A Survey of Endocrine Disrupting Chemicals
(EDCs) in Marine Sediments, Influents/Effluents
and Biosolids in Vancouver Wastewater
Treatment Plants (WWTPs)
by
Alvin Louie
B.Sc., Simon Fraser University, 2010
Project Submitted in Partial Fulfillment of the
Requirements for the Degree of
Master of Environmental Toxicology
in the
Department of Biological Sciences
Faculty of Sciences
Alvin Louie 2014
SIMON FRASER UNIVERSITY
Spring 2014
ii
Approval
Name: Alvin Louie
Degree: Master of Environmental Toxicology
Title of Project: A Survey of Endocrine Disrupting Chemicals (EDCs) in Marine Sediments, Influents/Effluents and Biosolids in Vancouver Wastewater Treatment Plants (WWTPs)
Examining Committee: Chair: Dr. Tony Williams Professor
Dr. Francis Law Senior Supervisor Professor
Dr. Chris Kennedy Supervisor Professor
Dr. Frank Gobas Internal Examiner Professor, School of Resource and Environmental Management
Date Defended:
April 10, 2014
iii
Partial Copyright Licence
iv
Abstract
The objective of this study was to apply a panel of yeast bioassays in the quantification
and identification of chemicals from 4 different classes of endocrine disrupting chemicals
(EDCs) in marine sediments and wastewater samples from Vancouver wastewater
treatment plants (WWTPs). In wastewater, estrogenic activity and AhR activity was
detected in the ng/L range, while no glucocorticoid or androgenic activity was detected.
There was also an observed general reduction in the estrogenic and AhR activity due to
wastewater treatment. In marine sediments, estrogenic activity was detected in the ng/g
range for 39% of samples, while AhR activity was detected in the µg/g range in 49% of
samples. GC-MS analysis of select samples identified bisphenol A (BPA) in both
wastewater and marine sediments, while dehydroabietic acid (DHAA) was found in only
marine sediments. Overall, the yeast bioassay is a useful tool for use in biomonitoring of
EDCs.
Keywords: Endocrine disrupting chemicals; Wastewater Treatment; Marine Sediments; Estrogens; Yeast Bioassay; AhR agonists
v
Dedication
To all my friends and family who have
supported me over the years
vi
Acknowledgements
Special thanks to my supervisory committee Dr. F. Law and Dr. C. Kennedy for their
guidance and to Metro Vancouver for their support in the completion of this project.
vii
Table of Contents
Approval .......................................................................................................................... ii Partial Copyright Licence ............................................................................................... iii Abstract .......................................................................................................................... iv Dedication ....................................................................................................................... v Acknowledgements ........................................................................................................ vi Table of Contents .......................................................................................................... vii List of Tables .................................................................................................................. ix List of Figures.................................................................................................................. x List of Acronyms ............................................................................................................. xi Glossary ........................................................................................................................ xii
Chapter 1. Introduction ............................................................................................... 1 1.1. Classes of EDCs .................................................................................................... 1
1.1.1. Estrogens .................................................................................................... 1 1.1.2. Androgens .................................................................................................. 3 1.1.3. Aryl Hydrocarbon Receptor (AhR) Agonists ................................................ 5 1.1.4. Glucocorticoids ........................................................................................... 7
1.2. EDCs and the Environment .................................................................................... 8 1.3. Methods for EDC Detection .................................................................................. 10 1.4. Research Objective and Study Area ..................................................................... 14
Chapter 2. Materials and Methods ........................................................................... 15 2.1. Sample Collection ................................................................................................ 15 2.2. Chemicals ............................................................................................................ 18 2.3. Chemical Standards and Media Solutions ............................................................ 19 2.4. Sample Extraction and Dilution ............................................................................. 19 2.5. Yeast Bioassay ..................................................................................................... 20 2.6. Calculation of Data ............................................................................................... 21 2.7. Statistical Analysis ................................................................................................ 22 2.8. GC-MS Analysis ................................................................................................... 23
Chapter 3. Results ..................................................................................................... 25 3.1. Glucocorticoid and Androgen Assays ................................................................... 25 3.2. E2 and AhR Assay Verification ............................................................................. 25 3.3. Effects of Storage ................................................................................................. 27 3.4. Wastewater Analysis for EDCs ............................................................................. 30
3.4.1. Estrogenic Chemicals ............................................................................... 30 3.4.2. AhR Agonists ............................................................................................ 32
3.5. Biosolid Analysis for EDCs ................................................................................... 34 3.5.1. Estrogenic Chemicals ............................................................................... 34 3.5.2. AhR Agonists ............................................................................................ 35
3.6. IDZ Analysis for EDCs .......................................................................................... 37
viii
3.7. Marine Sediment Analysis for EDCs ..................................................................... 38 3.7.1. Estrogenic Activity ..................................................................................... 38 3.7.2. AhR Activity .............................................................................................. 40
3.8. GC-MS Analysis ................................................................................................... 43
Chapter 4. Discussion ............................................................................................... 45 4.1. E2 and AhR Assay Verification and Effects of Storage ......................................... 45 4.2. EDCs in Wastewater Samples .............................................................................. 46
4.2.1. Estrogenic Chemicals ............................................................................... 46 4.2.2. AhR Agonists ............................................................................................ 50
4.3. EDCs in Biosolids ................................................................................................. 52 4.4. EDCs in IDZ Samples ........................................................................................... 53 4.5. EDCs in Marine Sediments ................................................................................... 55
4.5.1. Estrogenic Chemicals ............................................................................... 55 4.5.2. AhR Agonists ............................................................................................ 58
4.6. Non-Detection of Glucocorticoids and Androgens ................................................ 62 4.7. GC-MS Analysis for EDCs .................................................................................... 63 4.8. Application of the Yeast Bioassay ......................................................................... 67
References ................................................................................................................. 68 Appendix A. E2 and AhR Assay Results for Wastewater ....................................... 80 Appendix B. E2 and AhR Assay Results for Biosolids ........................................... 84 Appendix C. E2 and AhR Assay Results for IDZ .................................................... 86 Appendix D. E2 Assay Results for WWTP B Marine Sediments ............................ 88 Appendix E. E2 Assay Results for WWTP A Marine Sediments ............................ 89 Appendix F. AhR Assay Results for WWTP B Marine Sediments .......................... 90 Appendix G. AhR Assay Results for WWTP A Marine Sediments .......................... 91 Appendix H. GC-MS Library Searches for BPA and DHAA .................................... 92
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List of Tables
Table 1.1. Examples of Estrogenic Compounds ........................................................ 3
Table 1.2. Examples of Androgenic Compounds ...................................................... 5
Table 1.3. Examples of AhR Agonists ....................................................................... 6
Table 1.4. Examples of Glucocorticoids .................................................................... 8
Table 2.1. Characteristics of WWTPs Sampled ....................................................... 15
Table 2.2. Summary of the 4 Assays ...................................................................... 21
Table 2.3. MLODs of Bioassays for Aqueous Samples ........................................... 23
Table 3.1. Ranges of EEQs (ng/L) in WWTP Raw Influents .................................... 32
Table 3.2. Range of EEQs (ng/L) in WWTP Final Effluents ..................................... 32
Table 3.3. Range of NAPEQs (ng/L) in WWTP Raw Influents ................................. 34
Table 3.4. Ranges of NAPEQs (ng/L) in WWTP Final Effluents ............................. 34
Table 3.5. Summary of E2 Assay Results for Marine Sediments ............................ 39
Table 3.6. Summary of AhR Assay Results for Marine Sediments .......................... 42
Table 4.1. EEQs in WWTP Final Effluents from Other Studies ................................ 50
Table 4.2. NAPEQs in WWTP Final Effluents from Other Studies ........................... 51
Table 4.3. Relative Potency of Estrogenic Chemicals ............................................. 58
Table 4.4. PAH Toxic Equivalency Factors (TEF) ................................................... 61
x
List of Figures
Figure 2.1. Map of WWTP A Stations ....................................................................... 16
Figure 2.2. Map of WWTP B Stations ....................................................................... 17
Figure 3.1. E2 Assay Results of Spiked Distilled Water with 3 Different E2 Concentrations. ...................................................................................... 26
Figure 3.2. AhR Assay Results of Spiked Distilled Water with 3 Different NAP Concentrations. ...................................................................................... 26
Figure 3.3. Effects of Storage on EEQs of WWTP B Marine Sediments. .................. 27
Figure 3.4. Effects of Storage on EEQs of WWTP A Marine Sediments. .................. 28
Figure 3.5. Effects of Storage on NAPEQs of WWTP B Marine Sediments. ............. 29
Figure 3.6. Effects of Storage on NAPEQs of WWTP A Marine Sediments. ............. 29
Figure 3.7. E2 Assay Results of WWTP Raw Influents and Final Effluents. ............. 31
Figure 3.8. Ahr Assay Results of WWTP Raw Influents and Final Effluents. ............ 33
Figure 3.9. E2 Assay Results of WWTP Biosolids. .................................................. 35
Figure 3.10. AhR Assay Results of WWTP Biosolids. ................................................ 36
Figure 3.11. E2 Assay Results of WWTP C IDZ samples and Effluents from 2012. ...................................................................................................... 37
Figure 3.12. E2 Assay Results of WWTP B Marine Sediments. ................................. 39
Figure 3.13. E2 Assay Results of WWTP A Marine Sediments. ................................. 40
Figure 3.14. AhR Assay Results for WWTP B Marine Sediments. ............................. 42
Figure 3.15. AhR Assay Results for WWTP A Marine Sediments. ............................. 43
xi
List of Acronyms
%CV Percent coefficient of variation
AhR Aryl hydrocarbon receptor
AR Androgen receptor
ARNT Aryl hydrocarbon receptor nuclear translocator
CALUX Chemically activated luciferase expression
DHT Dihydrotestosterone
DOC Deoxycorticosterone
E2 17β-estradiol
EC Effective concentration
EDC Endocrine disrupting chemical
EEQ 17β-estradiol equivalent
ER Estrogen receptor
GC-MS Gas chromatography mass spectrometry
GR Glucocorticoid receptor
HAH Halogenated aromatic hydrocarbon
HPLC High performance liquid chromatography
IDZ Initial dilution zone
LOD Limit of detection
MLOD Method limit of detection
NAP β-naphthoflavone
NAPEQ β-naphthoflavone equivalent
PAH Polyaromatic hydrocarbon
PBDE Polybrominated diphenyl ethers
PCB Polychlorinated biphenyl
PCDD Polychlorinated dibenzo-p-dioxin
PCDF Polychlorinated dibenzofuran
SEM Standard error of the mean
T4 Thyroxine
WWTP Wastewater treatment plant
xii
Glossary
Effective concentration 50 (EC50)
The concentration of a drug, antibody, toxicant or other chemical which produces 50% of the maximal possible effect of that agonist after a specified exposure time
Endocrine disrupting chemical (EDC)
Chemicals that may interfere with the body’s endocrine system and produce adverse development, reproductive, neurological and/or immune effects in both humans and wildlife
17β-estradiol equivalents (EEQs)
The collective estrogenic potency of the chemical contents within a sample expressed in terms of ng 17β-estradiol/g or L
Initial dilution zone (IDZ)
IDZ extends the lesser (in any direction) of one-quarter of the waterbody width or 100-m radius around the outfall. Receiving water quality objectives and guidelines do not apply within the IDZ
β-naphthoflavone equivalents (NAPEQs)
The collective AhR potency of the chemical contents within a sample expressed in terms of ng β-naphthoflavone/g or L
1
Chapter 1. Introduction
The emergence of compounds capable of interfering with regular hormonal
pathways in living organisms has provided a new challenge for conventional toxicity
testing and the regulation of these compounds. Collectively classified as endocrine
disrupting chemicals (EDCs), these compounds do not belong in any one group of toxic
substances (e.g. pesticides, heavy metals, pharmaceuticals etc.), but rather contain
chemicals within all of these groups. In addition, EDCs do not behave in the manner that
traditional toxic substances do; where an incremental increase of the dose leads to an
increase in effect. In fact, many EDCs may exhibit an effect at low doses, but may have
no effect or a completely different effect at high doses (Vandenberg et al. 2012). This in
turn makes it difficult and sometimes inappropriate to extrapolate results from high dose
experiments to low dose effects. In particular, the extrapolation of high dose laboratory
experiments to effects in the environment where concentrations are expected to be
much lower.
1.1. Classes of EDCs
1.1.1. Estrogens
One of the main classes of EDCs is the estrogens and estrogen mimics. These
are compounds both natural and synthetic that are capable of inducing an effect similar
to that of the natural female hormone 17β-estradiol (E2). Other than E2, the most
common estrogens detected in the environment include the synthetic estrogen 17α-
ethynylestradiol (EE2), industrial surfactant nonylphenol (NP) and Bisphenol A (BPA) (a
compound widely used in the manufacturing of plastic products see Table 1.1)
(Ferguson et al. 2013, Lee et al. 2013). In addition to the synthetic estrogens mentioned,
2
there are also a large number of naturally occurring phytoestrogens that are present in
the environment due to the consumption, processing and degradation of plant material.
Compounds such as genistein, daidzein, biochanin A and formononetin are weak
estrogens found in plants such as soy and other legumes (Rocha et al. 2013, Sassi-
Messai et al. 2009).
Estrogens play an important role in the function and development of living
organisms through the regulation of genes associated with the estrogen receptor. When
estrogenic chemicals bind to the estrogen receptor, a receptor ligand complex is formed
and acts as a transcription factor that binds to the estrogen response elements on DNA.
This plays an important role in metabolism, behaviour as well as sexual development.
Therefore, any upset in the balance of estrogens within an organism may affect the
processes mentioned above.
One environmental effect often associated with estrogens found in the aquatic
environment is the feminization of male fish. Rainbow trout exposed to EE2 have been
reported to show increased feminization and vitellogenin production (Verslycke et al.
2002). A 7-year study on fathead minnows in the Experimental Lakes Area also showed
that chronic exposure to low concentrations (~2 ng/L) of EE2 led to the development of
intersex fish and adverse effects on gonadal development. It also showed that these
effects did have an effect on the reproductive success of fish and ultimately lead to the
collapse of the population in the lake (Kidd et al. 2007).
3
Table 1.1. Examples of Estrogenic Compounds
Estrogenic Compound Chemical Structure Use
17β-estradiol (E2)
Natural female hormone
17α-ethinyl estradiol (EE2)
Synthetic estrogen found in oral contraceptives
Bisphenol A (BPA)
Used in the manufacturing of certain plastics
Nonylphenol (NP)
Industrial surfactants and detergents
Genistein (GEN)
Natural phytoestrogen found in legumes such as soybeans
1.1.2. Androgens
Androgens are the primary group of male sex hormones. They are mainly
responsible for the development of secondary male sexual characteristics such as
muscle development and the inhibition of adipose tissue formation (Singh et al. 2006).
4
Therefore androgens are commonly found in farm animals as they may be used in the
promotion of animal growth (Schiffer et al. 2004). Common androgens include
trenbolone used in promotion of growth in livestock and the synthetic androgen
methyltestosterone which is often used in the treatment of androgen deficient men
(Table 1.2) (Morthorst et al. 2010 and Selzsam et al. 2005). Androgens exert their effect
through a mechanism similar to that of estrogens. Upon binding of an androgen, the
androgen receptor translocates to the nucleus of the cell and binds onto the section of
DNA known as the androgen response element. This in turn regulates the expression of
genes associated with androgens and the androgen receptor leading to effects
mentioned above.
In fish, exposure to androgens may cause different adverse effects. For example,
Zebrafish exposed to environmentally relevant concentrations of trenbolone exhibited
irreversible masculinisation as well as a skewed sex ratio tending towards males
(Morthorst et al. 2010). Fathead minnow exposed to feedlot effluents from concentrated
animal feeding operations containing potent androgens resulted in the defeminisation of
female fathead minnows (Orlando et al 2004). Androgens therefore, also represent an
important class of EDC capable of inducing adverse effects in aquatic organisms.
5
Table 1.2. Examples of Androgenic Compounds
Androgenic Compound Chemical Structure Use
Testosterone
Natural male hormone
Trenbolone
Synthetic androgen used mainly in livestock to increase muscle growth
Methyltestosterone
Synthetic androgen used to treat androgen deficiency
1.1.3. Aryl Hydrocarbon Receptor (AhR) Agonists
Agonists of the AhR found in the environment are most often associated with
industrial manufacturing or the combustion of oil or coal. Widely known AhR agonists
include chemicals such as polycyclic aromatic hydrocarbons (PAHs), halogenated
aromatic hydrocarbons (HAHs) such as polychlorinated biphenyls (PCBs) and
polychlorinated dibenzofurans (PCDFs) and polychlorinated dibenzo-p-dioxins (PCDDs)
(Denison et al. 2002). Examples of AhR agonists are listed in Table 1.3. Many of these
compounds are known for their acute toxicity and potent carcinogenicity. This is due to
the importance of the AhR in the regulation of xenobiotic metabolism. The binding of a
ligand to the AhR forms a receptor ligand complex that forms a heterodimeric complex
with the aryl hydrocarbon receptor nuclear translocator (ARNT). This complex regulates
the expression of metabolic genes such as CYP1A1 and CYP1A2 which increases the
breakdown of many AhR agonists. The metabolites of these agonists are quite often
6
toxic, leading to adverse effects within the cell (Ko et al. 1996, Martin and Klaasen
2010).
Table 1.3. Examples of AhR Agonists
AhR Agonist Chemical Structure Use
Benzo[a]pyrene
Component of coal tar, PAH byproduct of combustion of organic materials
Anthracene
Component of coal tar, used in the production of dyes
Chrysene
Component of coal tar, found in the wood preservative creosote
2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD)
Industrial byproduct
PCB 28
Industrial coolants, plasticizer
In addition to the acute toxic effects, agonists of the AhR can induce various
endocrine disrupting effects. White whales that were found to have been exposed to
PCBs had significantly reduced levels of thyroxine (T4), a hormone that contributes to
the regulation of metabolism and protein synthesis (Villanger et al. 2011). Killifish
exposed to benzo[a]pyrene, a potent carcinogen, had inhibited levels of the enzyme
aromatase, the enzyme that normally converts androgens into estrogens. This leads to
the interference of normal steroidogenesis within the fish and may lead to adverse
effects in development (Patel et al. 2009). Other than through the normal AhR signalling
7
pathway, agonists of the AhR may also induce endocrine disrupting effects through the
estrogen receptor pathway. Many PCBs have been shown to have an effect on estrogen
signalling through an AhR-ER crosstalk mechanism which will activate the estrogen
receptor (Calo et al. 2010). Some AhR agonists may therefore also be classified as
estrogenic chemicals as they are capable of mimicking the effects of E2. This further
highlights the difficulty of classifying EDCs as a whole, and predicting of biological
effects due to EDC exposure.
1.1.4. Glucocorticoids
Glucocorticoids are a class of steroid hormones that function mainly to suppress
the immune system, promote gluconeogenesis and regulate blood pressure (Kugathas
and Sumpter, 2011). They exert their action by binding to the glucocorticoid receptor
(GR) which up-regulates the expression of genes associated with the glucocorticoid
response element (GRE). This is similar to the mechanism by which estrogens and
androgens exert their effect within an organism. Due to the ability to suppress the
immune system, many synthetic and natural glucocorticoids are prescribed as anti-
inflammatory drugs, but this same immunosuppressant effect also has the potential to
harm organisms exposed to glucocorticoids in the environment (Kitaichi et al. 2010).
Glucocorticoids in the aquatic environment may induce several adverse effects to
fish. A study in fathead minnows exposed to the environmentally relevant concentrations
of synthetic glucocorticoids prednisolone and beclomethasone dipropionate reported an
increase in plasma glucose levels as well decreased levels of white blood cells. The
suppression of the immune system may increase the susceptibility of fish to parasitic
infections and other diseases which can have a large impact on the sustainability of fish
populations (Kugathas and Sumpter, 2011). Examples of glucocorticoids are listed in
Table 1.4.
8
Table 1.4. Examples of Glucocorticoids
Glucocorticoid Chemical Structure Use
Hydrocortisone
Natural stress hormone, increases blood sugar, suppresses immune system
Dexamethasone
Anti-inflammatory drug
Prednisone
Anti-inflammatory drug
1.2. EDCs and the Environment
There are 3 main anthropologenic sources by which EDCs may enter the
environment and potentially pose a risk to wildlife. This includes municipal wastewater
treatment plants (WWTPs), agricultural discharges and industrial effluents. First,
WWTPs are a known point source for the release of EDCs into the environment. Many
products being used today contain compounds that are known to be or suspected of
being EDCs. Daily use of pharmaceuticals such as oral contraceptives and personal
care products like lotions and creams in addition to the naturally excreted hormones
within human waste contributes to the load of EDCs entering a WWTP (Boyd et al.
2004). Even though WWTPs are not designed to remove EDCs from the wastewater,
microbial dependent treatments used in many WWTPs are capable of removing some
types of EDCs, more specifically 30-70% of estrogenic activity from the wastewater
9
(Johnson et al. 2007). Still, EDCs contained within the waters exiting the drains of the
average household may eventually reach the environment. It has been reported that the
synthetic estrogen EE2, a common EDC and the main component of oral contraceptives,
has been detected in aquatic environments at concentrations in the ng/L range (Wise et
al. 2011). These concentrations, although low, have the potential to induce adverse
behavioural effects in fish under laboratory conditions, including reduced aggression in
male zebrafish and fathead minnows, and reduced interactions between male spined
sticklebacks (Soffker and Tyler, 2012).
The second point source of EDC discharge is large agricultural and livestock
operation. Livestock such as cattle, pigs and goats excrete large amounts of natural
hormones in their wastes (Sarmah et al. 2006). In addition to the natural hormones,
growth hormones and other synthetic steroids administered to increase the growth in
these animals may also be excreted into the farm effluents (Schiffer et al. 2004).
Effluents from agricultural facilities are generally untreated and are directly discharged
into the environment. Agricultural operations may also use sewage sludge gathered from
WWTPs as a source of fertilizer due to their abundance in phosphate (Deeks et al.
2013). But since many EDCs are hydrophobic and have a tendency to bind onto organic
particles, EDCs may be concentrated in the sewage sludge during the treatment of
wastewater (Lee et al. 2004). There is therefore potential for EDCs in sewage sludge to
reach the aquatic environment through farm effluents, especially during rainy seasons.
The third source of EDCs in the environment are the effluents discharged from
industrial facilities which may contain a wide range of EDCs such as PAHs, PCBs,
PBDEs (polybrominated diphenyl ethers) and heavy metals (Hong et al. 2010). Despite
regulatory legislation and discharge permits that limit the release of these chemicals, the
persistent and bioaccumulative nature of these EDCs may lead to concentrations
capable of inducing adverse effects to humans and wildlife.
EDCs discharged into the environment from the sources mentioned above
typically enter surface waters posing a great risk to aquatic organisms. In general,
industrial EDCs such as PAHs and PCBs have long half-lives in water and sediments
ranging from months to years (Tansel et al. 2011). Natural and synthetic hormones
generally have shorter half lives in water and sediment, ranging from hours to days. For
10
example, the natural female hormone 17β-estradiol (E2) has a typical half life of
approximately 1 day in water, whereas the synthetic estrogen EE2, has a half life of 17
days (Jurgens et al. 2002). Even though hormones have much shorter half lives, the
constant release of effluents from WWTPs and agricultural operations leads to a
pseudo-persistence of these compounds in concentrations detectable in surface waters
(Moschet, 2009). Studies from Germany, Japan, Netherlands and Italy found E2
concentrations in surface water up to 27 ng/L (Ying et al. 2002).
Although concentrations of EDCs in surface water remain relatively low (ng/L
range) , many EDCs have high octanol water partition coefficients (logKow) and tend to
bind onto organic particles (Ying et al. 2002 and Nagpal, 1993). Many studies have
found detectable concentrations of EDCs in marine and river sediments even in areas
where the concentrations of EDCs in the surface water are not detectable (Peck et al.
2004, Hilscherova et al. 2002 and Levy et al. 2011). Sediments provide a sink where
hydrophobic EDCs may accumulate as the degradation rates of many EDCs is
substantially lower in sediments compared to surface water. In surface water, the
reported half life of E2 is approximately 1 day, whereas the half life in anaerobic
sediments increases to 70 days (Ying and Kookana, 2003). The accumulation of EDCs
in river and marine sediments poses an increased risk to benthic species that spend the
majority of the time in contact with the sediment. EDCs in sediments may also be
released back into the surface water, or the sediment itself may be resuspended into the
water column through processes such as bottom trawling, ultimately increasing the
exposure to other aquatic organisms. Thus, when river sediments collected from an
agriculturally intense watershed containing anti-estrogenic compounds were exposed to
female fathead minnows, defeminisation of the fish was apparent (Jeffries et al. 2011).
Sediments therefore represent a potential sink or source of EDCs in the environment.
1.3. Methods for EDC Detection
There are currently several commonly used methods in the detection of EDCs in
environmental samples. These include chemical analysis such as high performance
liquid chromatography (HPLC) or gas chromatography mass spectrometry (GC-MS), and
cell based assays such as the yeast screening assays and chemically activated
11
luciferase expression (CALUX) assays (Nie et al. 2009, Leusch et al. 2010). Each of
these methods have distinct advantages and disadvantages which makes the selection
of a method dependent on the questions being asked.
Chemical analysis is generally more sensitive compared to cell based assays. In
the detection of natural and synthetic estrogenics using high resolution GC-MS, the
limits of detection (LODs) were reported as low as the pg/L range (Nie et al. 2009). In
cell based assays, method limits of detection reported were between 0.1-5 ng/L
depending on the type of cell used (Leusch et al. 2010). In addition to high sensitivity,
chemical analysis can also identify the individual compounds within a mixture and
quantify the concentrations of the target compounds.
Although chemical analysis has many desirable advantages, it is not without
limitation. First and foremost, chemical analysis is expensive, meaning it is not an
economical choice when considering the large number of samples that must be tested
from the environment to reduce the effect of environmental variation on the quantification
of EDCs. Quite often, internal standards are also used in chemical analysis to improve
the accuracy of the results which further add to the cost when considering the potentially
large number of EDCs that may be included in environmental mixtures.
In addition to being costly, the use of chemical analysis also requires the
development of procedures to optimize the derivatization process for EDC detection (Nie
et al. 2009). With the wide variety of EDCs that may be in an environmental mixture,
different derivatization processes may be needed depending on the types of EDCs being
targeted in the analysis. This may increase the time required for sample preparation,
further increasing the cost. Even with optimized derivatization procedures, chemical
analysis can only detect chemicals which are known to be EDCs. If the endocrine
disrupting properties of a chemical present in a sample mixture is not known, it will not
be included in the results as it was not a targeted compound.
Cell based assays provide an alternative method to chemical analysis for the
detection of EDCs. General advantages of cell based assays include relatively simple
procedures, inexpensive when compared to chemical analysis, and quick turnover rates
which allows for the rapid screening of a large amount of samples at the same time
12
(Balsiger et al. 2010). But perhaps the biggest advantage of cell based assays is the
direct biological response that is measured in the assay. Cell based assays gives a
biological response based on the collective compounds within the mixture and therefore
takes into account potential chemical-chemical interactions. A measured biological
response also gives direct information on the potential effect of exposure to an organism
(Young, 2004). This is compared to chemical analysis which identifies and quantifies
individual compounds but gives no indication of the potential effects to an organism.
With all the advantages of cell based assays, there remain a few issues to
overcome. One of the main issues is the potential for toxicity of the sample to the cells
used in the assay. As environmental samples contain a mixture of chemicals, the
potential for highly polluted samples to contain chemicals that are toxic to the cells is
substantial (Leusch et al. 2010). This would require further cleanup procedures to
remove the toxic substances but may also reduce the levels of the target compounds
leading to an underestimation in the final result. The biological variability of cell based
assays have also lead to questions regarding the uncertainty when interpreting the
results, although adequate replication of experiments may help to overcome some of the
variation (Andersen et al. 1999).
The two main types of cell based assays are the yeast cell assays and
mammalian cell assays (Hilscherova et al. 2002, Bistan et al. 2011, Houtman et al. 2007,
Leusch et al. 2010 and Balsiger et al. 2010). Mammalian cells are generally more
sensitive to EDCs and therefore provide a lower limit of detection. They are also more
relevant in terms of equating the response seen in the assay to effects expected to be
seen in organisms that are exposed. This is due to the natural endogenous hormones
contained within the mammalian cell which may interact with the EDCs within the
sample, whereas yeast cells transformed to express the hormone receptor do not
contain a hormone system (Leusch et al. 2010). The drawbacks in using mammalian cell
based assays are the requirements of sample sterilization, longer incubation periods and
general higher costs compared to yeast based assays. Mammalian cells also naturally
express many different types of hormone receptors which may affect or interfere with the
expression of the reporter gene. Therefore, the response seen in the results of these
assays may not be based solely on the activity of the class of EDCs being targeted with
the assay (Balsiger et al. 2010). In comparison, yeast cells provide the benefit of shorter
13
incubation periods, lower costs and higher resistance to contamination with the trade-off
of being less sensitive. Yeast cells also provide the added advantage of fewer false
positives as endogenous hormones which may cause a false positive are not present.
Therefore, the response seen will be entirely dependent on the concentration of EDCs in
the sample activating the hormone receptor. Yeast bioassays have also been developed
to assay environmental samples without the need for extraction, concentration and
sterilization (Balsiger et al. 2010). The main disadvantage of yeast based assays
however, is that yeast cells genetically modified with the a human hormone receptor,
may not react the same way as a normal human cell when exposed to agonists that
should activate said receptor. For example, hydrocortisone is a potent agonist of the
human glucocorticoid receptor. This compound when exposed to yeast cells modified to
express the human glucocorticoid receptor induced virtually no response (Garabedian
and Yamamoto, 1992). This may be due to degradation of the compound by the yeast
cells or a decrease in the affinity of the receptor for these ligands. Either one of these
mechanisms may lead to underestimation of the concentrations of EDCs within the
sample. But it should be noted that the major EDCs that are expected to be found in the
environment are detectable using yeast based assays (Bistan et al. 2011, Balsiger et al
2010 and Hilscherova et al. 2002).
The disadvantages of chemical analysis and cell based assays make the use of
just one method insufficient when assessing the endocrine disrupting properties of an
environmental sample. Interestingly, the advantages of each method appear to
compensate for the disadvantage of the other. Cell based bioassays may be used to
screen a large number of samples to identify and prioritize highly polluted sites. While
chemical analysis can be done on the prioritized sites to identify the main chemicals of
potential concern. Therefore the use of both methods in the assessment of
environmental samples provides information that will lead to a more accurate
assessment of EDC concentrations in the sample as well as the chemicals most likely to
induce adverse effects to living organisms.
14
1.4. Research Objective and Study Area
There are many reports which link EDC exposure to adverse reproductive effects
and/or decline fish population (Verslycke et al. 2002 and Kidd et al. 2007). It is therefore
important to determine EDC concentrations in environmental samples, especially those
collected near WWTPs. To this end, our laboratory has compared the use of the yeast
estrogenic screening (YES) assay and the E-screen assay in the screening of influents
and effluents from WWTPs operated by Metro Vancouver for estrogenic chemicals
(Nelson et al. 2007). We have also used the YES assay to survey the concentrations of
estrogenic chemicals in WWTPs across Canada (Shieh et al. 2011) and to monitor
estrogenic chemicals in fish and shellfish samples from Pakistan (Hunter et al. 2012).
The main objectives of the current study were: (a) to apply a panel of yeast
bioassays in detecting and quantifying four different classes of EDCs (AhR agonists,
glucocorticoids, estrogenic and androgenic chemicals) in WWTP and environmental
samples, (b) to examine the effects of wastewater treatment on EDC concentrations in
the wastewater, de-watered biosolids, marine sediments, and initial dilution zone (IDZ)
boundary waters, (c) to identify compounds chemically in these samples, which may
contribute to the EDC activity of the bioassay, and (d) to conduct a preliminary risk
assessment of EDCs for marine sediments near the WWTPS based on the yeast
bioassay results. Hitherto, available sediment and wastewater guidelines are based on
the concentrations of single chemicals. Because the yeast bioassays are able to provide
a response for multitude of chemicals having a similar mode of action, they may be used
to develop guidelines for EDC mixtures.
15
Chapter 2. Materials and Methods
2.1. Sample Collection
Wastewater samples were collected from 5 different WWTPs coded A-E (Table
2.1) operated by Metro Vancouver using ISCO Avalanche refrigerated autosampler in
2012 and 2013. Twenty-four hour time-weighted composite wastewater samples were
taken over a period of at least 3 days and transferred to 1 L amber glass bottles. At the
time of collection of WWTP E samples in 2013, a disinfection trial was in progress which
resulted samples that have undergone a different treatment compared to the WWTP E
samples of 2012.
Table 2.1. Characteristics of WWTPs Sampled
WWTP Annual Volume Treated
(Billion L)
Population Served Sewage Treatment Process
A 32 180 000 Anaerobic Digestion
B 207 600 000 Anaerobic Digestion
C 175 1 000 000 Trickling Filters/Anaerobic Digestion
D 26 172 000 Trickling Filters/ Anaerobic Digestion
E 4.5 27 000 Trickling Filters/ Anaerobic Digestion
Dewatered bio-solid samples were also collected in from the storage tanks and
kept in 250 ml amber glass jars. However, biosolid samples were only collected from
WWTP A, WWTP C and WWTP D as WWTP B and WWTP E did not process solids at
16
their location. All samples were kept on ice and/or refrigerated at 4 oC before being
delivered to Simon Fraser University for extraction and analysis. Samples were
extracted within 48-72 h upon receipt, and not more than 96 hours from the time of
collection to minimize possible chemical degradation.
Figure 2.1. Map of WWTP A Stations Image provided by Metro Vancouver
17
Figure 2.2. Map of WWTP B Stations Image provided by Metro Vancouver
Marine sediment samples were collected in 2012 and 2013 by Metro
Vancouver’s consulting teams using a 0.1 m2 stainless steel Van Veen sampler
18
(McPherson et al. 2013a,b). At each station three grabs samples were collected. The top
2 cm of each grab was transferred to a stainless steel bowl where it was mixed until the
color and consistency was homogenous. Pre-cleaned 250 ml amber glass jars were
filled with sediment leaving no headspace. Samples were collected from the receiving
environment around the WWTP A and WWTP B outfalls at 16 stations each. In addition,
two stations were sampled in duplicate (fresh casts / not a split sample) for a total of 18
samples for each of the two programs. Station locations are mapped on Figures 2.1 and
2.2. All samples were kept on ice and/or stored at 4 oC before delivery to Simon Fraser
University within 72 h of sample collection. Samples were extracted within 72 h upon
receipt and assayed within 48 h after extraction to minimize possible chemical
degradation.
IDZ water samples were collected in 2012 by ENKON Environmental Limited for
Metro Vancouver using a 10-L or 12-L Teflon-lined “Go-Flow” sampler at the WWTP A
IDZ boundary at a target sampling depth of 15 m and WWTP C IDZ boundary at a target
sampling depth of 3-5 m. Pre-cleaned, 1 L amber glass bottles were filled leaving no
headspace. Five samples were collected from each IDZ boundary. One reference
sample was also collected for each program for a total of 12 samples. One IDZ boundary
sample was sampled in duplicate (ie. split sample). Final effluent samples were also
collected during the IDZ boundary sample collection at both WWTPs to provide a
comparison to the IDZ boundary samples. All samples collected were kept on ice before
delivery and stored at 4oC before extraction. Samples were extracted within 96 h of
collection and assayed within 48 h after extraction to minimize potential for chemical
degradation.
2.2. Chemicals
Unless otherwise stated, all chemicals were purchased from Sigma Aldrich
(Oakville, ON, Canada). The chemicals standards for the bioassays were: 17β-estradiol
(E2) for the estrogen receptor (ER) assay, β-naphthoflavone (NAP) for the aromatic
hydrocarbon receptor (AhR) assay, deoxycorticosterone (DOC) for the glucocorticoid
receptor (GR) assay and dihydrotestosterone (DHT) for the androgen receptor (AR)
assay.
19
L-Histidine (98% purity), L-leucine (98% purity), L-trytophan (98% purity), uracil
(99% purity), Difco yeast nitrogenous base w/o amino acids and ammonium sulphate
(BD Bioscience, Mississauga, ON, Canada), anhydrous dextrose (Merck Canada,
Kirkville, QC, Canada), synthetic complete amino acid dropout mix minus histidine,
leucine, uracil and tryptophan were purchased from MP Biomedicals, Solon, OH, USA.
2.3. Chemical Standards and Media Solutions
Stock solutions for the chemical standards were prepared in methanol at a
concentration of 2.72E+6 ng/ml and stored at -4 0C until use. New stock solutions were
prepared each month and tested in the assay once per week to confirm potency. Dilution
series for the standard stock solution ranging from 2.72E+2 ng/ml to 2.72E-4 ng/ml were
prepared for the bioassays. Agar and media were prepared according to Balsiger et al.
(2010) and differed in the yeast strain and the amino acids added to the culture medium.
For example, DSY-219 SC-UW referred to the DSY-219 yeast strain and the amino
acids not used in the culture medium, SC-UW therefore, refers to the media prepared
without uracil and tryptophan. The yeast strains and the culture media used in the
present study were: DSY-219 in SC-UW media for the ER assay, DSY-1345 in SC-UWH
media for the GR assay, DSY-1555 in SC-LUW media for the AR assay and MCY-038 in
SC-W media for the AhR assay. All yeast strains were kindly provided by Dr. Marc B.
Cox (University of Texas at El Paso).
2.4. Sample Extraction and Dilution
Wastewater samples were extracted according to Huang and Sedlak (2001). Fifty
ml of the wastewater sample were poured into clean 200 ml glass beakers. The C18
extraction discs (Empore 3M, London, ON, Canada) were preconditioned with 10 ml
methanol for 1min, followed by 10 mL of distilled water for 1min. The 50 ml wastewater
sample was filtered through the preconditioned extraction disc and eluted with 10 ml of
methanol after soaking for 2 min. The eluent was collected in a clean test tube and
evaporated to dryness under a gentle stream of nitrogen.
20
Biosolid and marine sediment samples were extracted using the methods
described by Temes et al. (2002). Five grams of the biosolid/marine sediment sample
was measured into a clean glass extraction tube. Ten ml of ethyl acetate was added into
the sample and shaken by hand for 2 min. The extraction tubes were then set on a
shaker at low for 10min before being centrifuged at 2000 rpm for another 10 min. The
ethyl acetate portion was collected in a clean test tube and the process was repeated
two more times for a total collection of 30 mL of ethyl acetate. This portion was
evaporated to dryness under a gentle stream of nitrogen. The evaporated residues were
reconstituted in 500 µl of methanol and stored at -4 oC until use.
As the extracts of the biosolid samples may contain sulphur and cause toxicity to
the yeast cells, a simple and rapid sulphur removal procedure described by Jensen et al.
(1977) was used to reduce the potential of this toxicity.
Dilutions series were prepared for each sample extract at 1.0, 0.8, 0.2, 0.02,
0.002 and 0.0002 of the original extract concentration before analysis.
2.5. Yeast Bioassay
The procedures for the yeast bioassay were modified from Balsiger et al. (2010).
Each of the yeast strains used in the assays contained a receptor for a particular class of
endocrine disrupting chemical (Estrogens, Androgens, Glucorticoids and Aromatic
Hydrocarbons). The receptors upon binding to an agonist in the test extract induced an
upregulation in the production of the β-galactosidase enzyme within the yeast cells. The
amount of β-galactosidase produced within the yeast cells was directly proportional to
the potency of the total estrogens, androgens, aromatic hydrocarbons or glucocorticoids
in the test extract. Upon addition of a buffer and substrate mixture, the yeast cells were
lysed resulting in the release of β-galactosidase which catalyzed a reaction with the
added substrate. The reaction produced UV light as a measurable signal. The UV light
intensity was proportional to the amount of β-galactosidase produced.
21
Table 2.2. Summary of the 4 Assays
Assay Type Standard Compound Yeast Strain Culture Media
Media used for Dilution
Estrogen 17β-estradiol DSY-219 SC-UW SC-UW
Androgen Dihydrotestosterone DSY-1555 SC-LUW SC-LUW
Glucocorticoid Deoxycorticosterone DSY-1345 SC-UWH SC-UWH
AhR Agonists Β-naphthoflavone MCY-038 SC-W SC-W w/ Galactose
H, L, U, and W represents histidine, leucine, uracil and tryptophan respectively. All media were made with dextrose as the sugar with the exception of the dilution media for the AhR assay where galactose is used.
The experimental procedures for the four assays were very similar but with
different yeast strains and culture medium used in each assay (Table 2.2). On the first
day, one colony of a yeast strain was inoculated into 10 ml of the culture medium. The
culture was incubated overnight at 30 oC with shaking. On the morning of day two, the
culture was diluted to an optical density of 0.08 at a wavelength of 600 nm. This diluted
culture was again incubated at 30 oC until an optical density of 0.1 at 600 nm was
reached. The incubation typically took 2-2.5 h. Upon the completion of the incubation, 1
μl of each concentration of the sample and standard dilution series were aliquotted onto
an opaque bottom 96 well cell culture plate followed by 100 μl of the yeast culture. The
contents of each well were mixed by pipetting gently up and down before incubation at
30 oC for 2 h. Several min before the completion of the incubation, Tropix Gal-screen
buffer was prepared by diluting the substrate with Buffer B at a ratio of 1:24 and kept on
ice until use. The mixture was added into each well of the 96 well plate in 100 μl aliquots
and mixed gently with a pipet before a final 2 h incubation at room temperature.
Following the last incubation, the plate was read on a Multilabel Plate Reader (Perkin
Elemer, Woodbridge, ON, Canada) to determine the UV activity induced by the sample
in each well. All samples were tested in triplicates.
2.6. Calculation of Data
The UV light intensities obtained from the plate reader were plotted as dose
response curves for both the standard and sample dilution series on Graphpad (La Jolla,
CA, USA) Prism 5. As the sample concentrations were unknown, the concentrations
22
were instead plotted as the dilution factors mentioned above (Section 2.4). From the
resulting dose-response curves, EC50s and the slopes of each curve were obtained. For
some samples, theundiluted extracts showed absorbance readings below the
background value indicating the presence of unknown chemicals which caused toxicity
to the yeast cells. These samples were not included in the calculation. Thus the EC from
samples not affected by toxicity were used to calculate the endocrine disrupting potency
of the samples with the equation from Lorenzen et al. (2004) The results were expressed
as endocrine disruptor equivalents where “endocrine disruptor” is one of the standard
compounds (β-naphthoflavone, 17β-estradiol, deoxycorticosterone or
dihydrotestosterone):
Below is an illustrative example to calculate β-naphthoflavone equivalents
(NAPEQ) in the AhR assay (Lorenzen et al. 2004):
NAPEQ (ng/ml) = [β-naphthoflavone EC50(ng/ml) / extract EC50 (unitless)] *
[volume of assay medium (ml) / (volume of extract tested (µl)] * [volume of stock
extract (µl) / volume of unknown water sample (ml)]. (1)
The EC50 obtained from the dose-response curves also were used to calculate
the EC20s and EC30s of both the sample and standard curves using the following
equation:
ECX = [X/(100-X)^(1/H)] * EC50 Where X is either 20 or 30 and H is the hill slope
of the curve. (2)
Using these values, the estimates from equation 1 using the EC20s, EC30s and
EC50s were averaged to take into account the linear portion of the sample and standard
curves providing a more accurate estimate of the sample potency.
2.7. Statistical Analysis
The final results were reported as the mean concentration equivalents of a
standard compound + standard error of the mean (SEM). Data <MLOD were graphed as
half of the MLOD value. To make further statistical comparisons, a Student’s t-test was
23
used to determine significance at p <0.05 for wastewater influents compared to effluents,
and year to year differences between marine sediment and biosolid samples. The
Pearson’s R Test was used to determine if there were relationships between the results
of each bioassay and also the measured EDC concentrations in marine sediments and
the distance from the WWTP outfall.
The LOD of each assay was taken as the EC20 of the standard curve because
the EC20 is the lowest concentration at which the assays can reliably differentiate from
background activity (Lorenzen et al. 2004). Using the EC20s as the LOD and the amount
of standard added to the sample, the method limit of detection (MLOD) for water was
determined in each yeast bioassay. Samples/replicates that tested <MLOD were
included in the calculation of mean EEQs as one half of the MLOD. An examination of
the limits of detection of our assays showed that they were generally within the ranges
reported in the literature (Table 2.3), with perhaps the exception of the glucocorticoid
assay where no comparable values could be found.
Table 2.3. MLODs of Bioassays for Aqueous Samples
Assay Current Study (ng/L) Other Studies (ng/L) Reference
Estrogen 1.28±0.26 0.1-5 Di Dea Bergamasco et al. (2011), Leusch et al. (2010)
Aromatic Hydrocarbon 50.5±10.1 49.9-59.1 Miller et al. (1997), Olivares et al. (2011)
Androgen 17.4±3.5 17.3-78.7 Bovee et al. (2007), Eldridge et al. (2007)
Glucocorticoid 94±19.0 N/A N/A
2.8. GC-MS Analysis
Sediment and WWTP final effluent samples with high EDC contents in the yeast
bioassays were also extracted and analyzed with GC-MS (Nie et al. 2009) which
consisted of a Model 7890A gas chromatograph and a model 5975C VL MSD mass
spectrometer (Agilent Technologies, USA). The carrier gas used was 99.99% helium at
a flow rate of 1.5 ml/min. The GC oven temperature was programmed to start at 100oC
24
for 1 minute before an increase to 200 oC at 10 oC/min, followed by an increase to 260
oC at 15 oC/min, and a final increase to 300 oC at 3 oC/min. The MS was operated in full
scan mode to determine the unknown compounds within the sample.
25
Chapter 3. Results
3.1. Glucocorticoid and Androgen Assays
All samples collected in 2012 were tested for glucocorticoids and androgenic
chemicals in addition to estrogenic chemicals and aromatic hydrocarbon receptor
agonists. All samples tested for glucocorticoid and androgen activity were <MLOD in
both assays.
In 2013, selected samples (WWTP A: 1, 3, 45, 49, 51, 52; WWTP B: 3, 7, 9, 16,
17, 18) containing the highest and lowest EEQs or NAPEQs from 2012 were assayed for
glucocorticoids and androgens to confirm the 2012 results. Again, samples tested in
2013 were <MLOD for both assays.
3.2. E2 and AhR Assay Verification
Distilled water samples spiked with three different concentrations of E2 and β-
naphthoflavone were extracted and assayed to examine the accuracy of the E2 and AhR
assays as well as the recovery rate of the extraction method. Results of the study
showed that assay-determined 17β-estradiol equivalents (ng/mL) and NAPEQs (ng/mL)
were very close to the actual E2 and β-naphthoflavone concentrations (Figure 3.1 and
3.2). In addition, the calculated percent coefficients of variation (% CV) for both assays
were used to assess the precision of the assays and the variability of the assays. For the
E2 assay, the %CV was 51.2, 47.6 and 56.6 for each of the three spiked concentrations.
For the AhR assays, %CVs was 15.4, 11.0 and 20.5 for each of the concentrations
tested. The %CVs calculated were similar across the 3 test concentrations for both
assays, suggesting that there was minimal plate-to-plate variation for each assay.
However, the mean %CV of 51.8% for the E2 assay indicated that there was a
considerable amount of variation in the estimated EEQs.
26
Figure 3.1. E2 Assay Results of Spiked Distilled Water with 3 Different E2 Concentrations.
Each point represents the mean ± SEM of three separate assays. Percent recovery in brackets.
Figure 3.2. AhR Assay Results of Spiked Distilled Water with 3 Different NAP Concentrations.
Each point represents the mean ± SEM of three separate assays. Percent recovery in brackets
27
3.3. Effects of Storage
As there is a period of time between sample collection and the running of the
assay, there is potential for degradation of target compounds which may affect the
results of the assay and/or the GC-MS analysis. Select marine sediment samples where
EDC activity was detected from 2012 for both WWTP A and WWTP B were assayed at
times approximately 1 month and 2 months after collection to determine the effects of
storage on the concentration of estrogenic and AhR activity. For the E2 assays (WWTP
A 3, 6, 10, 12, 13, 18, 45, 49, WWTP B 2, 9, 10, 11, 14, 15) estrogenic activity was still
detectable after 1 month of storage at 4oC. The WWTP A samples did not change
significantly (p < 0.05) in the estimated EEQ while the samples at WWTP B had a
statistically significant (p < 0.05) increase of 60% in EEQ after 1 month of storage.
Estrogenic activity was no longer detectable when assayed 2 months after the sample
collection date (Figures 3.3 and 3.4).
Figure 3.3. Effects of Storage on EEQs of WWTP B Marine Sediments. Bars represent the mean ± SEM of the 6 samples tested. An * indicates a significant effect of storage on the marine sediment samples (p < 0.05)
28
Figure 3.4. Effects of Storage on EEQs of WWTP A Marine Sediments. Bars represent the mean ± SEM of the 8 samples tested. An * indicates a significant effect of storage on the marine sediment samples (p < 0.05)
For the AhR assays (WWTP B 2, 14, 15, 16, WWTP A 3, 6, 10, 12, 13, 18, 45,
49), samples at both WWTP A and WWTP B showed no significant changes (p <0.05) in
the AhR activity even after 2 months of storage (Figures 3.5 and 3.6).
29
Figure 3.5. Effects of Storage on NAPEQs of WWTP B Marine Sediments. Bars represent the mean ± SEM of the 4 samples tested. An * indicates a significant effect of storage on the marine sediment samples (p < 0.05)
Figure 3.6. Effects of Storage on NAPEQs of WWTP A Marine Sediments. Bars represent the mean ± SEM of the 8 samples tested. An * indicates a significant effect of storage on the marine sediment samples (p < 0.05)
30
3.4. Wastewater Analysis for EDCs
3.4.1. Estrogenic Chemicals
The YES bioassay showed that there were detectable concentrations of
estrogenic chemicals in many raw influent and final effluent samples (Figure 3.7). Of the
5 WWTPs from which wastewater samples were collected, 3 WWTPs (WWTP A, WWTP
B, WWTP C) showed a statistically significant (p < 0.05) decrease of EEQs in the final
effluents when compared to the raw influents. In contrast the final effluents of WWTP D
had detectable estrogenic chemicals although the raw influents did not show any
estrogenic chemicals. Also, WWTP C was the only WWTP where raw influents and final
effluents had detected estrogenic activity in both sampling years with an average
decrease of 85% in the estrogenic activity of the final effluent compared to the raw
influent. At WWTP E, toxicity of the raw influent to the yeast cells was observed in both
sampling years (2012 and 2013), while toxicity due to the final effluent was only
observed in the first year (2012) of sampling. The reduction of toxicity in the second year
(2013) of sampling coincided with the implementation of a chlorination process which
occurred between the two sampling seasons. However, variation in samples, weather
and industrial activity may have also lead to the observed result. Regardless, estrogenic
chemicals were detected in these effluents, but whether the concentrations were above
or below that of the raw influents was unknown. Toxicity was also observed to a lesser
degree in the raw influents collected at WWTP A. This was seen in all raw influents in
the 2012 but only in samples collected on 2 of the 4 days sampled in 2013. This
suggests that there is variation in the wastewater quality input to and processed by the
WWTPs daily.
A year-to-year comparison of the results showed no obvious differences between
the estimated EEQs of the two sampling years other than the aforementioned changes
at WWTP E (Table 3.1 and 3.2). Although the 2013 WWTP B raw influents had
detectable estrogenic activity, the detection was only seen in 1 of the 3 sampling days.
The remaining WWTP B raw influents and final effluents showed EEQs <MLOD for both
sampling years. Collectively, the highest EEQs estimated in the raw influents were from
WWTP C, with an estimate of 4.8±0.21 ng/L in 2012 and 9.8±3.7 ng/L in 2013, whereas
the lowest estimates were <MLOD for both sampling years at WWTP D. Although
31
WWTP D raw influents had EEQs below the <MLOD, the final effluents had the highest
estimated EEQs out of all effluents tested for both sampling years with estimates of
1±0.005 ng/L in 2012 and 2±0.45 ng/L in 2013. The lowest EEQs seen in all of the final
effluents came from the WWTP B which were below <MLOD for both sampling years.
Figure 3.7. E2 Assay Results of WWTP Raw Influents and Final Effluents. Bars represent the mean ± s.e.m. of the samples collected over (n) sampling days. Each WWTP contains 4 bars where the first and third represent results from 2012, and second and fourth bars from 2013. An * indicates a significant difference between influent and effluent results (p < 0.05). A + indicates toxicity observed in at least one sample. Raw Influents , Final Effluents
32
Table 3.1. Ranges of EEQs (ng/L) in WWTP Raw Influents
Raw Influent EEQs (ng/L)
2012
Raw Influent EEQs (ng/L)
2013
Low High Mean Low High Mean
WWTP C 1.9 6.2 4.7 (5) 2.2 19 9.7 (5)
WWTP D <MLOD <MLOD <MLOD (3) <MLOD <MLOD <MLOD (4)
WWTP B <MLOD <MLOD <MLOD (3) <MLOD 5.7 1.4 (4)
WWTP E T T T (4) T T T (5)
WWTP A T T T (5) T 4.1 3.3 (5)
T= toxicity observed, (n) = number of samples
Table 3.2. Range of EEQs (ng/L) in WWTP Final Effluents
Final Effluent EEQs (ng/L)
2012
Final Effluent EEQs (ng/L)
2013
Low High Mean Low High Mean
WWTP C <MLOD 4.4 0.8 (5) 0.6 1.5 1.1 (5)
WWTP D 0.3 1.3 0.9 (3) <MLOD 2.4 2.0 (4)
WWTP B <MLOD <MLOD <MLOD (3) <MLOD <MLOD <MLOD (4)
WWTP E T T T (4) 1.0 2.4 1.6 (5)
WWTP A <MLOD <MLOD <MLOD (5) <MLOD <MLOD <MLOD (5)
T=toxicity observed, (n) = number of samples
3.4.2. AhR Agonists
The aromatic hydrocarbon receptor (AhR) assays detected AhR agonists present
in the raw influents and final effluents of the majority of samples tested (Figure 3.8).
WWTP C and WWTP D showed statistically significant (p < 0.05) decreases in the
estimated β-naphthoflavone equivalents (NAPEQs) in the final effluents when compared
33
to the raw influents, whereas WWTP B and WWTP A raw influents and final effluents
had estimated NAPEQs that were not significantly different. At WWTP C, the average
decrease in AhR activity in the final effluent was approximately 75%, whereas WWTP D
had a similar average decrease of 74%. The results of the AhR assay for WWTP E
samples were affected by toxicity much like the results of the E2 assay. Toxicity was
observed in all samples from WWTP E except for the effluents of 2013 which all tested
<MLOD. In 2012, the range of NAPEQs estimated ranged from <MLOD (WWTP B) to
234±1.8 ng/L (WWTP D) in the raw influents and <MLOD (WWTP B) to 197±17 ng/L
(WWTP A) in the final effluents. In 2013, estimates ranged from 81±52 ng/L (WWTP B)
to 434±217 ng/L (WWTP C) in the raw influents and <MLOD (WWTP E) to 88±3.4 ng/L
(WWTP D) in the final effluents.
A comparison of results between the 2012 and 2013 showed no significant
temporal differences (p < 0.05) in the NAPEQs estimated in samples from WWTP A,
WWTP C and WWTP D (Table 3.3 and 3.4). At WWTP B, differences were observed
between the 2012 and 2013 samples, as the raw influents and final effluents collected in
2012 all tested <MLOD, but AhR activity was detected in both in 2013.
Figure 3.8. Ahr Assay Results of WWTP Raw Influents and Final Effluents. Bars represent the mean ± s.e.m. of samples collected over (n) sampling days. Each WWTP contains 4 bars where the first and third represent results from year 2012, and second and fourth bars from 2013. An * indicates a significant difference between influent and effluent results (p < 0.05). A+ indicates toxicity observed in at least one sample. Raw Influents , Final Effluents
34
Table 3.3. Range of NAPEQs (ng/L) in WWTP Raw Influents
Raw Influent NAPEQs (ng/L)
Year 1
Raw Influent NAPEQs (ng/L)
Year 2
Low High Mean Low High Mean
WWTP C 58 232 146 (5) 65 971 432 (5)
WWTP D 220 244 234 (3) 105 274 172 (4)
WWTP B <MLOD <MLOD <MLOD (3) <MLOD 132 81 (4)
WWTP E T T T (4) T T T (5)
WWTP A T 266 144 (5) <MLOD 168 84 (5)
T=toxicity observed, (n) = number of samples
Table 3.4. Ranges of NAPEQs (ng/L) in WWTP Final Effluents
Final Effluent NAPEQs (ng/L)
Year 1
Final Effluent NAPEQs (ng/L)
Year 2
Low High Mean Low High Mean
WWTP C <MLOD 131 49 (5) <MLOD 77 50 (5)
WWTP D <MLOD <MLOD <MLOD (3) 82.37 96 88 (4)
WWTP B <MLOD <MLOD <MLOD (3) <MLOD 121 44 (4)
WWTP E T T T (4) <MLOD <MLOD <MLOD (5)
WWTP A <MLOD 303 198 (5) <MLOD 101 80 (5)
T=toxicity observed, (n) = number of samples
3.5. Biosolid Analysis for EDCs
3.5.1. Estrogenic Chemicals
The biosolids from WWTP A, WWTP C and WWTP D all showed estrogenic
activity based on the E2 yeast assay (Figure 3.9). Of the three WWTPs, biosolid
35
samples from WWTP D appeared to contain the highest average estrogenic activity with
EEQs of 45±6.3 ng/g and 48±8.6 ng/g in 2012 and 2013 respectively. These were
comparable to WWTP C with EEQs of 11±6.5 ng/g in year 2012 and 28.2±4.9 ng/g in
2013. At WWTP A, the toxicity that was observed in some of the wastewater samples
was also seen in the biosolid samples. Of the 4 samples collected at WWTP A in each of
the sampling years, only 1 of the 4 samples in 2012 had detectable estrogenic activity
where the other 3 exhibited toxicity. All samples in 2013 showed toxicity to the yeast
cells. However, the detection had an estimated EEQ of 123.7 ng/g, which was the
highest estimate among all the biosolid samples assayed. Overall, there is no significant
year to year (p < 0.05) variation in EEQs estimated in the samples collected at each
WWTP.
Figure 3.9. E2 Assay Results of WWTP Biosolids. Bars represent the mean of 3-4 samples ± s.e.m. of samples collected over 3-4 sampling days. Each WWTP contains 2 bars where the first represents 2012 and the second represents 2013. An * indicates a significant difference between year 1 and year 2 estimates (p < 0.05). + indicates toxicity observed in at least one sample
3.5.2. AhR Agonists
The results of the AhR assay for the biosolids differed to the E2 assay results
markedly (Figure 3.10). Although toxicity was also seen in some of the WWTP A
samples, 3 of the 4 samples in 2012 had detectable AhR activity, while only 1 showed
36
toxicity. In 2013, 1 sample had detectable AhR activity while the other 3 showed toxicity.
The NAPEQs estimated in the WWTP A biosolid samples ranged from 6716 ng/g to
9174 ng/g, which were higher than the NAPEQs seen in the other two WWTPs. WWTP
C biosolids contained the second highest estimates of NAPEQs at 3373±1342 ng/g in
2012 and 3081±728 ng/g in 2013. WWTP D biosolid samples contained the lowest
estimated NAPEQs of the three WWTPs with 672±142 ng/g in 2012 and 1450±271 ng/g
in 2013.
When the results were compared year to year, there was no significant variation
(p < 0.05) between 2012 and 2013 samples collected from WWTP C and WWTP D. In
terms of NAPEQs estimated, there was also no significant variation seen at WWTP A (p
< 0.05), but there appeared to be an increase in toxicity to the yeast cells in the biosolid
samples collected during 2013. This difference was seen for both the E2 and AhR
assays for the biosolid samples.
Figure 3.10. AhR Assay Results of WWTP Biosolids. Bars represent the mean of 3-4 samples ± s.e.m. of samples collected over 3-4 sampling days. Each WWTP contains 2 bars where the first represents year 2012 and the second represents 2013. * indicates a significant difference between year 1 and year 2 estimates (p < 0.05). + indicates toxicity observed in at least one sample
37
3.6. IDZ Analysis for EDCs
Water samples collected at the IDZ boundary in the receiving environment of
WWTP A and WWTP C were assayed for both AhR agonists and estrogenic chemicals.
At both the WWTP A and WWTP C IDZs, no AhR activity was detected by the AhR
assay for the 5 stations sampled (data not shown). For the E2 assay, 2 stations in the
WWTP C IDZ had detectable estrogenic activity with 3.38±1.2 and 1.83±0.3 ng EEQs/L
(Figure 3.11) whereas no estrogenic activity was detected in WWTP A IDZ samples
(Data not shown). The EEQs estimated from WWTP C IDZ samples were higher than
the average EEQ of 0.6±0.08 ng/L seen in the final effluents of WWTP C indicating that
there are likely other sources contributing to the estrogenic activity seen at the WWTP C
IDZ.
Figure 3.11. E2 Assay Results of WWTP C IDZ samples and Effluents from 2012. Bars represent the mean ± s.e.m. of three lab assay replicates. * indicates a significant difference between effluent and IDZ results (p < 0.05)
38
3.7. Marine Sediment Analysis for EDCs
3.7.1. Estrogenic Activity
In 2012, 8 of the 16 stations or 50% of the stations from WWTP B stations had
detectable estrogenic activity, while only 6 of 16 stations or 38% of the stations of
WWTP A showed estrogenic activity. Although there were more detects in the WWTP B
stations, the EEQs at WWTP A stations were much higher than those of WWTP B
stations. The EEQs at WWTP B stations ranged from 3.8±0.9 - 16.5±4.8 ng/g with a
median value of 9.3 ng/g (Figure 3.12) while the EEQs at WWTP A stations ranged from
1.6±0.3 – 51.9±11 ng/g with a median value of 28.5 ng/g (Figure 3.13).
In 2013, 7 of the 16 stations or 44% of the stations from WWTP B showed
estrogenic activity, while 6 of the 16 stations or 38% of the stations showed estrogenic
activity at WWTP A. Much like the first sampling year, the marine sediments from WWTP
A had higher EEQs compared to those from WWTP B. The EEQs in WWTP B marine
sediments ranged from 7.2±2.1 - 12.4±5.5 ng/g with a median value of 9.5 ng/g, while
the EEQs of WWTP A samples ranged from 12.0±2.7 - 49.4±17.4 ng/g, with a median
value of 27.0 ng/g.
When the results of the two sampling years were compared, there was some
yearly variation seen in both study areas. At WWTP B, 4 stations had detections in both
sampling years with estimated EEQs that were not significantly (p < 0.05) different
between the two years. In addition, 4 stations had a decrease in EEQ to <MLOD
between 2012 and 2013, whereas 3 stations that tested <MLOD in 2012 showed
detectable estrogenic activity in 2013. Similar to WWTP B, WWTP A also had 4 stations
that had detectable estrogenic activity in both sampling years with no significant (p <
0.05) difference in the EEQs between the two sampling years. There were also 2
stations that had an increase in the EEQ from <MLOD and 2 station that had a decrease
in EEQ to <MLOD. Overall, there was no significant correlation between the EEQs at
each station and the distance of the station from the WWTP outfalls of either WWTP (R2
= 0.006 for WWTP B and 0.018 for WWTP A) .
39
Figure 3.12. E2 Assay Results of WWTP B Marine Sediments. Bars represent the mean ± s.e.m. of three assay replicates. * indicates a significant difference between 2012 and 2013 results (p < 0.05). Year 1 , Year 2
Table 3.5. Summary of E2 Assay Results for Marine Sediments
WWTP B WWTP A
Year 1 Year 2 Year 1 Year 2
% of Samples Positive 50% 44% 38% 38%
Highest EEQ (ng/g) 16 12 52 49
Lowest EEQ (ng/g) 3.8 7.2 1.6 12
Median EEQ (ng/g) 9.3 9.5 29 27
# of Sites Positive for both Years
4/16 (25%) 4/16 (25%)
40
Figure 3.13. E2 Assay Results of WWTP A Marine Sediments. Bars represent the mean ± s.e.m. of three assay replicates. * indicates a significant difference between 2012 and 2013 results (p < 0.05). Year 1 , Year 2
3.7.2. AhR Activity
Although the E2 assay results showed a similar number of stations that had
detectable estrogenic activity at both study areas, the AhR assay results showed
considerable differences between WWTP B and WWTP A. In 2012, only 2 of the 16
(13%) WWTP B stations showed detectable AhR activity with NAPEQs of 394±49 ng/g
and 533±18 ng/g (Figure 3.14). This was comparable to the 11 out of the 16 (69%)
WWTP A stations that showed NAPEQs ranging from 264±137 - 1575±229 ng/g with a
median value of 506 ng/g (Figure 3.15).
In 2013, there was a similar trend: 7 out of 16 (44%) WWTP B stations had
detectable AhR activity while WWTP A had 12 of 16 (75%) stations that showed AhR
activity. At WWTP B the NAPEQs ranged from 104±28 - 519±82 ng/g with a median of
445 ng/g, while at WWTP A, NAPEQs ranged from 288±76 - 1396±653 ng/g and a
41
median of 558 ng/g. Overall, the range of NAPEQs for each study area remained similar
from year 1 to year 2 but the number of stations with AhR activity increased in the
second year. Of the 16 stations sampled at WWTP B, 6 stations had an increase in
NAPEQs from <MLOD in 2012, while only 1 stations showed a decrease to <MLOD.
There was also 1 station where AhR activity was detected in both sampling years with
estimated NAPEQs that were not significantly different (p < 0.05).
Altogether, 9 stations at WWTP A had AhR activity detected in both sampling
years. Of these 9 stations, 1 had a significant (p < 0.05) decrease, while the remaining 8
do not have NAPEQs that changed significantly (p < 0.05) from year to year. There were
2 stations where AhR activity was detected in 2012 and 2 other stations where AhR
activity was detected in 2013. Overall, there is no significant correlation between the
NAPEQ estimated and the distance of the station from the WWTP A outfall (R2 = 0.230).
Although the stations located on the north side of the outer Burrard Inlet tended to have
higher AhR activity detection rates for both sampling years, but this was not related to
the WWTP effluent as the NAPEQs estimated did not change significantly (p < 0.05) with
increasing distance from the outfall. At WWTP B, there was no significant relationship
between the NAPEQs estimated and the distance from the WWTP B outfall at station 9
(R2 = .07). Only WWTP B station 16, which was considered a background reference
station had detectable AhR activity in both sampling years. Although WWTP B stations
4, 5, 6 and 8 also had detectable AhR activity in 2013, they were all non-detects in 2012.
It was therefore unclear if the NAPEQs estimated in these stations were influenced by
the WWTP B outfall.
When the results of the E2 and AhR assays for the marine sediments (Figures
3.12 and 3.13) were compared, there was no significant correlation between the
detected EEQs and NAPEQs at either WWTP B (R2 = 0.019) or WWTP A (R2 = 0.152)
samples. Of the 16 WWTP B stations, only 4 stations had detectable estrogenic and
AhR activity in the same sampling year. At WWTP A, 6 of 16 stations had detectable
estrogenic and AhR activity in the same sampling year.
42
Figure 3.14. AhR Assay Results for WWTP B Marine Sediments. Bars represent the mean ± s.e.m. of three assay replicates. * indicates a significant difference between 2012 and 2013 results (p < 0.05). Year 1 , Year 2
Table 3.6. Summary of AhR Assay Results for Marine Sediments
WWTP B WWTP A
Year 1 Year 2 Year 1 Year 2
% of Samples Positive 13% 44% 69% 75%
Highest NAPEQ (ng/g) 533 606 1575 1396
Lowest NAPEQ (ng/g) 394 355 264 288
Median NAPEQ (ng/g) 464 466 506 558
# of Sites Positive for both Years
1/16 (6%) 9/16 (56%)
43
Figure 3.15. AhR Assay Results for WWTP A Marine Sediments. Bars represent the mean ± s.e.m. of three assay replicates. * indicates a significant difference between 2012 and 2013 results (p < 0.05). Year 1 , Year 2
3.8. GC-MS Analysis
Selected samples from 2013 were analyzed for estrogenic and AhR agonists with
GC-MS based on the detection of such chemicals in the yeast bioassay. Several
samples were combined to form a composite sample to potentially increase the
probability of identifying EDCs in the extract. The samples tested were wastewater
effluents from WWTP C (composite of 4 effluents collected), wastewater effluents from
WWTP A (composite of 4 effluents collected), marine sediments from WWTP B
(composite of stations 9, 10 16) and marine sediments from WWTP A (composite of
stations 5, 45, 49). GC-MS analysis of composite final effluents from WWTP C and
WWTP A effluent samples and marine sediments from WWTP B and WWTP A regions
identified BPA in all four composite samples.
44
Dehydroabietic acid was identified in both the marine sediment samples from
WWTP B and WWTP A but not detected in the WWTP C and WWTP A composite final
effluents.
45
Chapter 4. Discussion
4.1. E2 and AhR Assay Verification and Effects of Storage
The distilled water samples spiked with a chemical standard showed that the
extraction method had a 65% recovery (Figure 3.1 and 3.2). However, the samples
showed a large variation in the estimated EEQs, especially when the spiked
concentration was very low. As such the 700% E2 recovery in the 1 ng/mL sample
(Figure 3.1) most likely is due to variation in the assay replicates with a 52% mean %CV.
Therefore, sufficient replication is needed by the assay to minimize the effect of variation
and allow for the removal of assay outliers. In comparison, the AhR assay has been
shown to be both precise and accurate with an average recovery rate of 95% (Figure
3.2) across the three spiked concentrations with %CVs ranging from 10-20%.
Previous work in our laboratory shows that sample extracts can be stored at 4oC
without significant (p < 0.05) changes in the estimated EEQs for a period of
approximately 2 weeks, while wastewater samples under the same storage conditions
maintain similar EEQs for up to 2 months (Shieh, 2011). As the samples in this study
have been extracted and assayed well within this timeframe, the effects of storage on
the E2 assay results are expected to be small.
Based on the results of the stored marine sediments (Figs. 3.3-3.6), storage
effect on the assay results are minimal as estimated EEQs and NAPEQs do not change
significantly (p < 0.05) for at least 1 month with the exception of the estrogenic activity of
WWTP B marine sediments. Since all assays have been run within one week after
receiving the samples, the overall effect of storage on the assay results is expected to
be small. An increase in estrogenic activity in WWTP B samples after storage may be
due to the conversion of less active estrogenic chemicals to more active estrogenic
compounds such as the de-conjugation of glucoronic acid and/or sulfate conjugates of
estrogens by bacteria and other micro-organism which (Lee et a. 2004). There was also
46
an apparent change in the top layer of the sediment, which suggests that oxidation of
compounds in the sediment may also contribute to the increased estrogenicity.
For the AhR assay (Figures 3.5 and 3.6), there is no significant (p < 0.05) effect
of storage on the NAPEQs estimated in marine sediments even after 2 months of
storage which is not surprising as many AhR agonists are persistent in the environment
due to their structural stability and resistance to degradation.
4.2. EDCs in Wastewater Samples
4.2.1. Estrogenic Chemicals
WWTP treatment may increase or decrease the estrogenicity of the final effluent
discharged into the environment. In this study, three WWTPs (WWTP A, WWTP B and
WWTP C) show an apparent decrease in the estrogenicity of the final effluent in
comparison to the raw influent, while WWTP D is the only WWTP with a statistically
significant increase in estrogenicity in the final effluent (Figure 3.7). The 85% decrease
in estrogenicity seen at WWTP C may be due to contributions from residential areas
making up most of the load. As such, the majority of the estrogenic compounds in the
wastewater would be natural hormones such as E2 of which up to 98% can be removed
by conventional wastewater treatment methods (Servos et al. 2005). At WWTP D, the
EEQs in the final effluent were the highest of the five WWTPs tested despite estimated
EEQs <MLOD in the raw influents of both sampling years (Tables 3.1 and 3.2). Several
factors may contribute to the non-detects of EEQs in the raw influents. One factor is the
reduced bioavailability of estrogenic compounds to the yeast cells due to the conjugation
of estrogenic compounds or sorption to organic particles (Atkinson et al. 2012). As the
yeast assay is based on the binding of free estrogens onto the receptor to induce a
response, any change in the chemical form or bioavailability of the estrogens may
prevent the yeast cells from detecting the estrogenic substance. However, subsequent
treatment of the wastewater may lead to de-conjugation or release of the estrogenic
compounds from organic particles through reactions catalyzed by bacteria in the
wastewater (D’Ascenzo et al. 2003). This will result in an increase in the estrogenicity
detected in the final effluents. A second factor may be the presence of anti-estrogenic
47
compounds which may bind to the estrogen receptor but do not induce a response,
therefore preventing the estrogenic chemicals from exerting their effect. Anti-estrogenic
compounds have been reported in wastewater samples and may include pharmaceutical
compounds such as the anti-breast cancer drug tamoxifen (Fang et al. 2012). If
wastewater treatment is able to remove the anti-estrogenic compounds from the raw
influents, then the yeast cells would be able to detect estrogenic compounds in the
effluent samples.
At WWTP B, only 1 raw influent sample shows estrogenic activity while all other
raw influents and final effluents show <MLOD activity (Tables 3.1 and 3.2). This
suggests that there is some daily variation in the EEQ contents of the influents.
Therefore, a carefully designed sampling program, such as the one used in this study
(sampling spans multiple days, 24 h composite samples, duplicate samples etc.), should
be included to account for these variations. The results at WWTP B also show that
population size may not be the best indicator of the estrogenicity of a given WWTP.
WWTP C which serves approximately 1 million residents shows the highest EEQs in raw
influents among all samples with detectable estrogenic activity. WWTP B, which serves
over 600000 people, has only 1 sample with detectable estrogenic activity over the two
sampling years. In addition, WWTP A and WWTP D which are similar to each other in
the population size served and volume of wastewater processed, have very different
estrogenic profiles. Whereas WWTP A has raw influents that show detectable estrogenic
activity and final effluents with no detectable estrogenic activity, the opposite is observed
at WWTP D. The variation seen in the EEQs of the raw influent across all 5 WWTPs
therefore suggests that the composition of the wastewater received by each WWTP is
very different (Figure 3.7). This means the type of estrogenic compounds in the raw
influent is more likely to have the greatest effect on the estrogenicity of the final effluent
because different estrogenic compounds are reduced to different extents (Ye et al.
2012). The use of the yeast bioassay alone to assess and compare the effectiveness of
different wastewater treatment methods does not seem appropriate if the composition of
estrogenic chemicals in raw influents differ among the WWTPs. In other words, two
WWTPs employing the same treatment methods would show different effectiveness in
the reduction of estrogenic activity in the wastewater if one WWTP has raw influent
containing mainly natural estrogens which are quite readily removed (Servos et al. 2005)
48
while the other WWTP has raw influent containing compounds such as perfluorooctane
sulfonate (PFOS) and perfluorooctanoic acid (PFOA) which are not readily removed by
conventional wastewater treatment methods (Rattanaoudom et al. 2012).
At WWTP E, the toxicity affects the results of both sampling years (Tables 3.1
and 3.2). As a result, I am only able to obtain results for the final effluent of the second
sampling year. Although WWTP E services only 27000 people, it has an EEQ in the
effluent similar to those of WWTP C and WWTP D. This may be due to contributions of
estrogenic chemicals from industrial and/or agricultural sources. Again, this suggests the
population size alone is not a good indicator of estrogenicity. The source and type of
estrogenic compounds may be more important factors to consider.
Overall, the range of assay EEQs in the final effluents of the five WWTPs
servicing the Greater Vancouver Area is within the range of EEQs reported in other
studies (Table 4.1) and appears to be at the lower end of the range. It may simply be
that estrogenicity is relatively low in the effluents of Vancouver WWTPs, but difference in
sampling time and methodology among the many studies may have an effect on the
estimated estrogenicity. Twenty-four hour composites, 8 hour composites and grab
samples collected at different times of the day are likely to have different estrogenic
compositions because of population movement during the day and industrial/other
contributions to the raw influents of the WWTPs (Johnson et al. 2000). Although the
EEQs estimated in the raw influents are very different among the 5 WWTPs, the average
EEQs in the final effluents of the WWTPs where estrogenic activity is detected are
surprisingly similar. The detected effluent EEQ concentration range (0.32±0.002 -
4.41±0.8 ng/L) is within the reported range of EEQs which have resulted in adverse
effects such as feminization of fish (Kidd et al. 2007), and reduction of gonadal growth
and development of secondary sexual characteristics (Pawlowski et al. 2004). However,
the adverse effects listed here are likely to occur only if the sample consists mainly of
EE2. Furthermore, the actual concentrations in the surface water are likely to be much
lower due to the dilution of the effluent in the receiving environment.
Previous YES studies involving the same 5 WWTPs from our laboratory have
found that EEQs in the final effluent may range from 30-1400 ng/L (Nelson et al. 2007).
These EEQs differ to the current results by several orders of magnitude. A possible
49
explanation for the difference in the results may be that the composition of the
wastewater differs due to dilution effect of precipitation, changes in the sources or
treatment methods of wastewater and/or variation in the sensitivity of the assays used in
the studies. In addition, a change in the extraction and assay method may also
contribute to the difference in the detected EEQs of these studies. Most notably, Nelson
et al. (2007) extracted total sample volumes of 1 L using liquid-liquid extraction
compared to just 50 mL using solid-phase extraction in the current study. The EEQs
estimated by Nelson et al. (2007) include results from both the YES assay and the E-
SCREEN assay which would lead to higher estimated EEQs because the E-SCREEN
assay which uses a human breast cancer cell line, generally produces EEQs that vary
from the EEQ of the YES assay by up to 4 fold higher. Although the present assay EEQs
are not consistent with results of the previous study, they are very similar to the range of
chemical concentrations determined by chemical analyses (0.5-4.0 ng/L) (Nelson et al.
2007). A second study from our laboratory looking at wastewater effluents of 13 WWTPs
across Canada reported a range of EEQs of 1.55-54.1 ng/L and a mean EEQ of 16.8
ng/L (Shieh, 2011), which is similar to the range of EEQs reported here.
Although the toxicity seen in samples from WWTP A and WWTP E affected the
results, the samples affected are mostly raw influent samples. This suggests that
wastewater treatment has lead to a reduction in compound(s) that contribute to the
observed toxicity. As a result, there is likely to be little or no effect of toxicity on the
EEQs detected in the final effluents.
50
Table 4.1. EEQs in WWTP Final Effluents from Other Studies
Country Range of EEQs (ng/L) in Final Effluent Reference
Canada 0.32-4.41 Current Study
Canada 1.55-54.1 Shieh, 2011
Canada 0.2-14.7 Servos et al. 2005
China 1.28-3.26 Fang et al. 2012
Portugal 0.95-24.2 Sousa et al. 2010
United Kingdom 0.28-13.8 Baynes et al. 2012
4.2.2. AhR Agonists
The AhR assay of wastewater samples indicates that AhR activity was reduced
in the five WWTPs (Figure 3.8). Apparent reduction averages about 75% at WWTP C
and 74% at WWTP D which is comparable to the 73-96% reduction seen in WWTPs in
France (Dagnino et al 2010). The NAPEQs in the final effluents are within the range of
those reported in other studies (Table 4.2). Although the AhR activity is reduced
significantly (p < 0.05), the tendency for AhR agonists to bind onto organic compounds
may affect estimation of the actual NAPEQ concentrations in the final effluents. In
addition to the dissolved phase, WWTP final effluents also contain suspended solids
which have not been removed from wastewater during the treatment process. Therefore,
AhR agonists may be bound to the suspended solid particles and discharged into the
environment along with the final effluent. Ultimately, this leads to an underestimation of
the actual concentrations discharged into the environment (Allinson et al. 2011).
At WWTP E, toxicity affects the results of the AhR assay much like the E2 assay,
but at WWTP A there is less toxicity seen as only 1 raw influent sample shows signs of
toxicity (Tables 3.3 and 3.4). As the same sample extract is used in the AhR and E2
assays, it is likely that the yeast used in the AhR assay is much more resistant to toxicity
compared to the yeast used in the E2 assay. This may be a product of the difference
51
between the ages of the yeast culture plates used, or differences in sensitivity to certain
chemicals between the two yeast strains.
The fact that some unknown compounds in a WWTP sample have the potential
of inducing toxicity to yeast cells means that they may cause adverse effects to wildlife if
discharged into the environment. However, the absence of toxicity seen in the 2013
WWTP E effluent samples suggests that wastewater treatment may have removed most
of the toxic compounds or that there are daily/seasonal variations in the input of the
toxic compound into the wastewater influent. Further research is needed to identify the
chemicals that caused toxicity in the bioassays.
There are very few studies on the removal efficiency of AhR activity in WWTP
samples. The NAPEQs estimated in the wastewater samples are of less importance
compare to the types of AhR agonists present. In particular, dioxin and dioxin like
chemicals such as PCBs and PCDDs are known to be potent toxins that can induce a
range of adverse effects from reproductive to developmental disorders (Janosek et al.
2006). Regardless, the range of NAPEQs seen in the final effluents of this study is
comparable to those found in Germany and Australia (Table 4.2). Whether these
concentrations will lead to adverse effects in wildlife will depend on factors such as the
type of AhR agonist in the effluent and whether these compounds are persistent or
bioaccumulative.
Table 4.2. NAPEQs in WWTP Final Effluents from Other Studies
Country Range of NAPEQs (ng/L) in Final Effluent
Reference
Canada 45-302 Current Study
Australia 16-279 Allinson et al. 2011
Germany 387-741 Stalter et al. 2011
52
4.3. EDCs in Biosolids
Bacteria and other micro-organisms are used in WWTPs to remove nutrients
from wastewater and to degrade organic compounds which may include some EDCs
(Johnson et al. 2007). Degradation of EDCs by micro-organisms likely contributes to the
apparent reduction of estrogenic and AhR activity in wastewater, but it is unlikely to
account for all of the 70-90% reduction seen in the current and other studies (Stalter et
al. 2011 and Dagnino et al. 2010). Primary treatment of wastewater involves the removal
of solids and other organic particles which are later processed into biosolids. As many
EDCs are likely to be lipophilic and adsorbed onto the particulates and/or suspended
particles during wastewater treatment, the removal of these will also take EDCs out of
the wastewater. This means that the apparent reduction of AhR and estrogenic activity
seen in the wastewater is not all due to complete removal, but may be in the biosolids
produced at the WWTPs (Lorenzen et al. 2004). Continued treatment of biosolids at the
WWTP can lead to a further reduction in the concentrations of EDCs through processes
such as microbial degradation, but little work with the yeast bioassay has been
conducted in this area due to the potential for toxicity to the yeast cells (Citulski and
Farahbakhsh. 2010).
The biosolid samples from the 3 WWTPs all show detectable concentrations of
estrogenic chemicals and AhR agonists (Figures 3.9 and 3.10). At WWTP C, the
apparent reduction of both estrogenic and AhR activity in the wastewater and the
detection of both in biosolids support the idea that not all of the apparent reduction seen
in the wastewater is due to complete removal and/or microbial degradation. At WWTP D,
the raw influents do not have detectable estrogenic activity in the E2 assay (Figure 3.7),
but the biosolids do contain detectable concentrations of estrogenic chemicals (Figure
3.9). A possible explanation for this is that the estrogenic chemicals are already bound to
organic particles in the wastewater before entering the WWTP. The removal of these
particles during primary treatment would collect the estrogenic chemicals into the
biosolids (Dagnino et al. 2010), while reactions catalyzed by bacteria may cause the
release of estrogenic chemicals from the bound particle or deconjugation of estrogenic
chemicals leading the detections seen in the final effluents.
53
The biosolids at WWTP A show signs of toxicity much like the wastewater
influents. The toxic compounds are likely removed from the wastewater and collected in
the biosolids leading to the observed toxicity. In the 2013 biosolid samples, there is an
increase in toxicity in the biosolid samples correlating to decrease in toxicity seen in the
wastewater samples. There may have been an increase in the removal of the toxic
compounds from the wastewater into the 2013 biosolid samples leading to an increase
in toxicity in the biosolid samples and/or a lower toxic compound concentration in the
wastewater. In either case, biosolids are a sink for EDCs and other compounds which
need to be considered in any assessment as they are frequently applied as fertilizer in
agricultural operations (Deeks et al. 2013).
Overall, the biosolid samples at WWTP A contain the highest concentrations of
both AhR and estrogenic activity among the 3 WWTPs (Figures 3.9 and 3.10). The
EEQs (R2 = 0.44) and NAPEQs (R2 = 0.04) estimated do not have a significant
correlation with the population size served (Table 2.1). Rather the main factors most
likely to affect the concentrations of EDCs in the biosolids are retention time, treatment
temperature, oxygen availability and other factors affecting micro-organism growth and
metabolism (Wilson et al. 2011).
4.4. EDCs in IDZ Samples
At the IDZ boundary of WWTP A, neither AhR nor estrogenic activity are
detected in the water samples (data not shown), suggesting that the EDCs detected in
the final effluent are diluted to <MLOD in the receiving environment. Although the yeast
bioassay does not detect any estrogenic or AhR activity in the IDZ water samples, a
chemical analysis study conducted by Metro Vancouver shows low concentrations of
estrogenic compounds and PAHs (Enkon, 2013a). However, common estrogenic
compounds such as NP, E2 and EE2 are either not detected, or if detected, do not meet
criteria for quantification (NDR). Of the 19 PAHs included in the 2012 WWTP A IDZ
study (Enkon, 2013a), all are below available CCME water quality guidelines. The
concentrations of individual PAHs ranged from < 0.01- < 0.05 µg/L. These results are
consistent with the non-detects seen in the present E2 and AhR assays. The
corresponding E2 and AhR effluent activity is <MLOD (except in 2012 for AHR), and
54
would be further reduced using an average dilution factor of 250:1 at WWTP A IDZ
(Enkon, 2013a).
At the WWTP C IDZ, 2 of the 5 stations have detectable estrogenic activity
(Figure 3.11) while no stations have detectable concentrations of AhR agonists (data not
shown). The assumption that concentrations of EDCs in wastewater effluents would be
diluted to concentrations below detection limits is not always appropriate. Areas where
water flow may be reduced or where the water is relatively enclosed can lead to the
accumulation of EDCs in the water and a reduction in the dilution effect (Allinson et al.
2011). The average predicted dilution at the WWTP C IDZ boundary is 40:1 under low
river flows and 60:1 under high river flows, compared to the ~250:1 predicted average
dilution at the WWTP A IDZ boundary. The estimated dilution at the WWTP C IDZ
boundary during the sampling events on March 6 and March 14 ranged from 25:1 to
110:1 and 13:1 to 59:1, respectively (Enkon 2013b). However, based on E2 and AhR
activities in these effluent grab samples and the 24-h composite samples (Figures 3.7,
3.8 and 3.11), the concentration at the WWTP C IDZ boundary would be predicted to be
<MLOD for these dilutions and the worst case minimum dilution of 7:1
Other studies also have reported estrogenic activity in the receiving waters of
WWTPs. Tang et al. (2012) have shown EEQs ranging from 1.05-17.60 ng/L in China,
Ferguson et al. (2013) have reported a range of EEQs from 2.95-18.9 ng/L in Australia,
while Jones-Lepp et al. (2012) have reported a range of EEQs from 0.04-2.4 ng/L in the
United States. Our estimates of EEQs in the WWTP C IDZ samples ranged from
1.83±0.3 - 3.38±1.2 ng/L for the 2 of 5 samples with detectable estrogenic activity.
Interestingly, these EEQs are higher than the average EEQ seen in the corresponding
WWTP final effluent of 1.16±0.1 ng/L. This is suggestive of sources upstream such as
agricultural operations that may have contributed to the estrogenic activity observed in
the samples from the IDZ. The 2013 WWTP C IDZ study identifies several estrogenic
compounds within the IDZ water sample, including NP (100 - 110 ng/L), E2 (1.88 - 2.59
ng/L), EE2 ( < 0.405 – NDR < 0.839 ng/L) and E1 (8.93 - 11.9 ng/L). Although the
concentrations of these estrogenic compounds in the WWTP C IDZ are comparatively
higher than those at the WWTP A IDZ, they do not exceed the CCME water quality
guidelines as the freshwater guideline for nonylphenol is 1000 ng/L.
55
4.5. EDCs in Marine Sediments
4.5.1. Estrogenic Chemicals
The mouth of the Fraser River is an area where large volumes of sediments are
deposited from upstream sources. It is therefore expected that EDCs which bind to
sediment particles will be deposited here as well. At both the WWTP A and WWTP B,
~40% of the marine sediment samples collected had detectable concentrations of
estrogenic activity (Figures 3.12 and 3.13), with EEQs ranging from 1.6±0.3 - 51.9±11
ng/g (Table 3.5). Our range of estimated EEQs are comparable to those from studies in
China which has reported EEQs ranging from 5.44-36.72 ng/g (Chen et al. 2012) and
9.8-101 ng/g (Zhao et al. 2011) as well as a study in Germany which has reported
values of 15-23 ng/g (Schmitt et al. 2012) in marine sediment. But our results differ by up
to several orders of magnitude when compared to studies that examined riverine
sediments which reported values of 0.001-1.2 ng/g in the Czech Republic (Hilscherova
et al. 2002) and 0.022-0.029 ng/g in the United Kingdom (Peck et al. 2004). The
difference in EEQs between marine and riverine sediments may be attributed to the flow
of the river carrying suspended organic particles and sediments downstream where it is
deposited in the estuary. As EDCs are likely bound onto these particles, they are carried
downstream and deposited in the estuary as well (Ferguson et al. 2013).
A comparison of the EEQs in wastewater effluent demonstrates that both WWTP
A and WWTP B have no detectable estrogenic activity in the final effluents for both
sampling years (Figure 3.3). This suggests that the estrogenic activity seen in the
marine sediments may not have come from the effluents of the WWTPs. However, Peck
et al. (2004) have reported that even in areas where surface water and final effluents
show low to non-detectable concentrations of estrogenic activity, the sediments in the
receiving environment may still show detectable estrogenic activity. It is likely that the
overall estrogenic activity detected at both WWTP A and WWTP B are due in part to the
effluents discharged from WWTPs in addition to other sources from upstream such as
agricultural and industrial operations.
Results of the marine sediments show that E2 activity is detected more often in
WWTP B samples, than WWTP A samples, while the activity tends to be lower at
56
WWTP B (Figures 3.12 and 3.13). The difference in results between these two sites is
explainable by the EDC sources upstream and the geographic location. Both the Burrard
Inlet and the Fraser River receive discharges from different industries. In addition, the
Fraser River may also receive estrogenic chemicals from cattle farms and agricultural
operations. These and other factors such as the persistence of the compounds,
tendency of the compounds to bind onto organic particles and/or the concentrations of
discharged estrogenic compounds may have affected the concentrations of estrogenic
activity detected in the marine sediments downstream. The different geographic location
of the two sites may have also affected the estrogenic activity seen in the marine
sediments. WWTP B discharges into the Strait of Georgia leading to a larger dispersal of
the effluent. In addition, the Fraser River flows into three main arms before meeting the
Strait of Georgia. This may lead to the dispersal of upstream estrogenic compounds
from the Fraser River over a much wider area in the WWTP B region, resulting in a
larger number of detections but lower EEQs in the marine sediments. In contrast, at
WWTP A, the final effluent is discharged into the Burrard Inlet which is a partially
enclosed waterway, and also has other potential sources of EDCs. Together with the
inflow of water from the Strait of Georgia and the binding of EDCs to sediment particles,
EDCs may have accumulated within a smaller area around the entry of the Burrard Inlet.
This may explain why relatively higher concentrations of estrogenic activity are observed
in the few detections in marine sediment samples of WWTP A compared to WWTP B.
Overall, results of the E2 assay on marine sediments for both WWTP B and
WWTP A (Figures 3.12 and 3.13) confirm other studies that marine sediments around
WWTPs may contain EDC contaminants (Peck et al. 2004 and Ferguson et al. 2013). As
EDCs accumulate in the marine sediments, they pose not only risks to benthic
organisms that live in contact with the marine sediments, but also result in a potential
source of EDCs as the EDCs may be re-introduced back into the water column if they
are re-suspended by tidal movements or shipping activity (Gomes et al. 2011 and
Ferguson et al. 2013). It is therefore important to monitor estrogenic activity in marine
sediments and not focus solely on industrial/WWTP/agricultural effluents and/or surface
waters.
A comparison of the EEQs measured by the yeast bioassay and the chemical
EEQs calculated using the relative potencies (Table 4.3) for E1, E2, E3, EE2, NP,
57
equilin, equilenin, mestranol, 17α-estradiol and 17α-dihydroequilin which are detected in
the 2012 sediments effects survey (McPherson et al. 2013a,b) shows that chemical
EEQs are lower compare to the YES bioassay EEQs. Whereas the bioassay EEQs may
range from 1.6±0.3 - 51.9±11 ng/g (Table 3.5) and only show detectable estrogenic
activity in ~40% of the marine sediments using the yeast assay (Figures 3.12 and 3.13),
chemical EEQs may range from 0.574-3.964 ng/g and estrogenic chemicals are
detected in all of the marine sediments from WWTP A and WWTP B. In addition, WWTP
A marine sediments have lower chemical EEQs which range from 0.574-2.844 ng/g with
a median of 0.947 ng/g when compare to WWTP B where chemical EEQs range from
2.412-3.964 ng/g with a median of 3.471 ng/g. This result differs to the yeast assay,
where the bioassay EEQs at WWTP A are generally high than those at WWTP B. The
difference between the bioassay EEQs and chemical EEQs may be due to other
estrogenic compounds within the sediments that are not measured by the chemical
analysis. As the bioassay EEQ is a collective response of the yeast to all of the
estrogens in the sample including possible interactions, it is expected to be higher when
compared to chemical EEQs which are calculated with only the known detected
estrogenic chemicals and does not take into account possible chemical interactions.
Although the chemical EEQs do not completely agree with the bioassay EEQs, the
narrow range of chemical EEQs at both WWTP B and WWTP A also show no significant
relationship between the chemical EEQs measured and the distance of the station from
the outfall (WWTP B R2 = 0.163, WWTP A R2 = 0.057) which is consistent with the
bioassay results.
58
Table 4.3. Relative Potency of Estrogenic Chemicals
Chemical Relative Potency References
17β-estradiol 1
Blair et al. 2000, Kuhl 1998.
Estrone 0.073
Estriol 0.097
17α-estradiol 0.030
Equilin 0.400
17α-dihydroequilin 0.180
Equilenin 0.070
Mestranol 0.022
17α-ethynylestradiol 2
Nonylphenol 0.0003
4.5.2. AhR Agonists
The AhR assay results of the marine sediments differ to the E2 assay results; the
number of samples where AhR activity is detected, is higher in WWTP A samples
(~73%) than WWTP B samples (~25%) (Figures 3.14 and 3.15). The WWTP A samples
also have higher average NAPEQ which are not surprising considering the final effluents
of WWTP A have the highest AhR activity among the 5 WWTPs when detected (i.e.,
only 3 samples are > MLOD) (Table 3.4). Although AhR agonists in the WWTP final
effluent may have contributed to the AhR activity seen in the marine sediment samples,
there are other possible sources. For example, the Burrard Inlet is home to one of the
busiest ports in North America with a large volume of ship traffic. Combustion emissions
as well as transport of coals and petroleum products may have introduced PAHs into the
water that eventually settled in the marine sediments (Soclo et al. 2000). It is likely that a
59
large portion of the AhR activity seen in the WWTP A marine sediment is related to the
ship traffic in Burrard Inlet.
In addition to the higher AhR activity in the samples at WWTP A, a large volume
of ship traffic may also increase the disturbance to the marine sediments. Re-
suspension of the sediment and changes in water flow may cause movements of
contaminant bound sediments leading to some of the year to year variation in results
seen at WWTP A. At WWTP B, there is less ship traffic so it is unlikely that the year to
year variation seen here is due to anthropogenic disturbances. The open waters at
WWTP B are more likely susceptible to tidal movements which may have caused the re-
suspension and movement of sediments from one site to another (Gomes et al. 2011).
Overall, the range of NAPEQs (264±137 - 1575±229 ng/g) estimated by the
yeast bioassay (Table 3.6) are within the range of total PAHs concentrations calculated
from the chemical analytical results reported in the 2012 Metro Vancouver WWTP outfall
sediments effects survey (McPherson et al. 2013 a,b). At WWTP A, total PAHs range
from 341 to 1772 ng/g with a median of 988 ng/g while at WWTP B, total PAHs reported
ranged from 144 to 781 ng/g with a median of 202 ng/g (McPherson et al. 2013a,b). A
screening level risk assessment based on the yeast assay NAPEQs is conducted after
converting them to benzo[a]pyrene equivalents (BAPEQs) and comparing the results
with the Canadian Sediment Quality Guidelines (CSQGs) for benzo[a]pyrene. Based on
the EC50s, EC30s and EC20s of the standard curves for benzo[a]pyrene and β-
naphthoflavone in the AhR assay, it is determined that benzo[a]pyrene is approximately
3.5 times more potent than β-naphthoflavone, yielding a relative potency factor of 0.285
for NAP. Of the combined fourteen samples where AhR activity was detected (2 WWTP
B, 12 WWTP A) in 2012, BAPEQs range from 85-479 ng/g with a median of 144 ng/g.
Moreover, 13 of the 14 estimated BAPEQs are above the interim CSQG value for
benzo[a]pyrene in marine sediment (88.8 ng/g), although all of them were well below the
probable effects level (concentration above which adverse effects are expected to occur
frequently) of 763 ng/g (CCME, 1999). In 2013, 21 marine sediment samples showed
detectable AhR activity in the yeast bioassay with BAPEQs ranging from 82-398 ng/g
with a median of 133 ng/g. Of the 21 positives results, 18 have an estimated BAPEQs
above the interim CSQG value, although all of them are well below the probably effects
level. Based on the results of the screening level risk assessment study, it is concluded
60
that there may be potential risks for adverse effects for aquatic organisms exposed to
WWTP A marine sediments. To compare the assay BAPEQs to chemical BAPEQs,
measured concentrations of individual PAHs from the 2012 Metro Vancouver WWTP
Outfall sediments effects survey (McPherson et al. 2013 a,b) are converted to BAPEQs
using PAH toxic equivalency factors (Table 4.4). The chemical BAPEQs of the 16
WWTP B stations range from 17-109 ng/g with a median of 28 ng/g, and only one
station is above the CSQG. The 16 WWTP A stations however, have chemical BAPEQs
ranging from 27-265 ng/g with a median of 155 ng/g, and 13 stations are above the
CSQG. Although the chemical BAPEQs are lower than the bioassay BAPEQs, the
general trend for both datasets show benzo(a)pyrene equivalent concentrations above
the CSQG value in WWTP A marine sediments. The conclusion from both datasets is
that there is a potential for adverse effects occurring in aquatic organisms exposed to
AhR agonists such as PAHs in WWTP A marine sediments, while there is minimal risk
for adverse effects occurring in aquatic organisms exposed in WWTP B marine
sediments.
61
Table 4.4. PAH Toxic Equivalency Factors (TEF)
PAH TEF References
Naphthalene 0
ATSDR, 2009
Acenaphthylene 0.001
Acenaphthene 0.001
Fluorene 0.001
Phenanthrene 0.001
Fluoranthene 0.001
Anthracene 0.01
Pyrene 0.001
Benz[a]anthracene 0.1
Chrysene 0.001
Benzo[b/j/k]fluoranthene 0.01
Benzo[e]pyrene 1.001
Benzo[a]pyrene 1
Perylene 0
Dibenz[a,h]anthracene 1
Indeno[1,2,3-cd]pyrene 0.1
Benzo[ghi]perylene 0.01
1-Methylnaphthalene 0
2-Methylnaphthalene 0
2,6-Dimethylphenanthrene 0.001
62
Very few studies have examined the AhR activity in marine sediments using
yeast based assays, making it difficult to compare our results with other studies.
However, several studies have looked at the total PAH content in marine sediments.
Tolosa et al. (1996) have reported total PAH ranges of 420-760 ng/g and 1200-2400
ng/g in two French coastal regions, Grimalt et al. (1984) have shown total PAH
concentrations of 1300-2300 ng/g in Spain. Wakeham et al. (1996) report an average of
total PAH concentration of 1500 ng/g in the marine sediments of Romania and Bates et
al. (1984) show there is an average of 1100 ng/g total PAHs in marine sediments of the
USA. Total sediment PAH concentrations are typically high in urban coastal regions and
low in more remote waters (Fernandez et al. 1999). Nevertheless, the range of NAPEQs
in the present study is comparable to the total PAHs seen in the other studies.
In many marine and river sediments PAH studies, samples are collected from
areas known to be contaminated by high industrial actvity. Total PAH ranges of 84.4-
14938 ng/g have been reported in China (Guo et al. 2007), 1132-39951 ng/g in the
Czech Republic (Hilscherova et al. 2002), 13000-18000 ng/g in Poland (Fernandez et al.
1999) and 206-9570 ng/g in Finland (Leskinen et al. 2008). On average, total PAHs
values are higher in areas where industrial operations discharge into enclosed water
bodies such as lakes (Fernandez et al. 1999). Therefore the range of AhR activity
reported in the present study is at the low range of contamination compared to other
studies, but the types of PAHs and other AhR agonists contained in sediments still
needs to be considered when assessing the potential risk and effects of exposure of the
sediment to living organisms as different AhR agonists exert different effects (Giesy et
al. 2002).
4.6. Non-Detection of Glucocorticoids and Androgens
The non-detection of androgens and glucocorticoids in the water and sediment
samples (data not shown) is interesting as numerous studies have reported the
presence of both androgens and glucocorticoids in WWTP samples (Leusch et al. 2006,
Van der Linden et al. 2008 and Chang et al. 2011). It is estimated that androgens also
63
make up the majority of steroidal hormones found in WWTP effluents (Chang et al.
2011) However, there have also been reports of the absence of androgenic activity in
WWTP samples and the presence of anti-androgenic compounds in both WWTPs and
marine sediments (Mnif et al. 2012, Fang et al. 2012 and Zhao et al. 2011). There are a
number of compounds that are potentially anti-androgenic. In addition to anti-androgenic
drugs like flutamide, some PAHs are also known to be anti-androgenic. Sediments
containing PAHs have been reported to mask the androgenic effect in the yeast
androgen assay. It has been shown that when sample extracts were fractionated and the
PAH portion was removed, the extract showed detection of androgenic activity. The
presence of PAHs in the samples may have masked the androgenic activity of the
samples (Weiss et al. 2009). Future studies using the yeast bioassay should consider
fractionation of samples to assist in determining the presence of androgen activity.
The non-detects with regards to glucocorticoids may be due to low
concentrations in wastewater and sediments. It is possible that further concentration of
the sample may lead to detection of glucocorticoid activity (Mnif et al. 2012). This may
be due to different physicochemical properties of the glucocorticoids . For example,
compounds such as hydrocortisone are expected to bind onto organic particles based on
log Koc values, whereas other compounds such as dexamethasone are expected to stay
in the aqueous phase (Pubchem, 2013). Separation of glucocorticoid mixtures into the
aqueous and organic phases may lower the glucocorticoid activity leading to the
observed non-detects. Future studies should focus on the development of an extraction
method which is specifically designed for glucocorticoids.
4.7. GC-MS Analysis for EDCs
GC-MS analysis was unable to detect natural estrogenic compounds such as E2
in the wastewater effluents (WWTP A and WWTP C) and sediment (WWTP A and
WWTP B) samples analyzed. However, a synthetic estrogenic chemical, BPA, is found
in WWTP A and WWTP C effluents as well as marine sediments from the WWTP A and
WWTP B region (Appendix H). BPA was not detected in a pilot study in 2011 that
reported BPA between <489 to < 746 ng/L in the effluent and <471 to <474 ng/L at the
IDZ of WWTP A. However, BPA concentrations in the reference sample, travel blank
64
and field blank also range from <478 to <500 ng/L (Enkon 2012). In addition, the marine
sediments had concentrations of BPA ranging from <394 to <439 ng/g at WWTP A and
<470 to <501 ng/g at WWTP B (Golder 2012 a,b). Therefore, BPA is not likely to
contribute significantly to the overall detected EEQs even if the BPA concentration were
equal to the detection limit assuming a relative potency of 0.00009 (Li et al. 2004).
Although public awareness of BPA as a potentially toxic substance to humans
has increased in recent years, and production of products containing BPA has
decreased, BPA is still used in the manufacturing of many plastic products. Other
studies have also reported the presence of BPA in WWTP effluents and marine
sediments due to the incomplete removal of BPA from wastewater treatment (Lee et al.
2013 and Ye et al. 2012). BPA removal rates in conventional WWTPs ranged from 65-
79% compared to the 85-99% removal of natural estrogenic hormones such as estrone
(E1), E2 and estriol (E3) (Ye et al. 2012). Moreover, a previous study from our laboratory
using gas chromatograph-high resolution mass spectrometer (GC-HRMS) has reported
the detection of a large number of estrogenic compounds including the natural estrogens
E1 (1.3-27.2 ng/L), E2 (0.1-11.2 ng/L) and E3 (≤ 4.9-8.9 ng/L) as well as industrial
estrogenic compounds like nonylphenol (207.5-1287.3 ng/L) and BPA (2.9-61.1 ng/L)
(Nelson et al. 2007). The discrepancy in the results between our current and previous
studies is likely due to the higher sensitivity of the GC-HRMS used in the earlier study
and the generally low concentrations of different estrogenic compounds in the
wastewater effluents. Although the current study is unable to detect estrogenic
compounds other than BPA using GC-MSD, our previous study detected the presence of
numerous estrogenic compounds using GC-HRMS in wastewater effluents.
The presence of BPA in the environment is of concern as numerous studies have
reported adverse effects associated with BPA exposure. These include interference with
sexual development and behaviour in rats (Kubo et al. 2003), reduction in the number of
offspring in Daphnia (Jeong et al. 2013) and interference with reproduction and
development in the fathead minnow (Staples et al. 2011) among others. Staples et al.
(2011) have reported a chronic 444 day no observed effect concentration (NOEC) of 16
µg BPA/L on F2 hatching success which is equivalent to an EEQ of 1.44 ng/L relative
potency (Li et al. 2004). This NOEC is below the EEQs measured in the IDZ samples of
1.83 and 3.38 ng/L, but given that the reported BPA concentrations in the effluents and
65
IDZ samples are in the ng/L range and well below the NOEC of 16 µg BPA/L, it is
unlikely for BPA to pose a significant risk to aquatic organisms. However, it is possible
that other estrogenic chemicals may accumulate in the marine sediment in
concentrations that may induce adverse effects in benthic organisms.
All marine sediments and wastewater effluents used in the GC-MSD analysis had
detections of AhR activity in the yeast AhR bioassay, but GC-MSD analysis failed to
identify any PAHs or other potential AhR agonists. This may be due to the use of the full
scan mode in our GC-MS analysis as opposed to the selective ion monitoring mode
(SIM). As full scan sets the instrument to detect a wider range of unknowns, it is less
sensitive compared to the SIM mode which programs the instrument to look for specific
unknowns and therefore has a lower detection limit. However, previous studies
conducted by Metro Vancouver from 2000-2009 at WWTP B and 2006-2009 at WWTP A
have identified PAHs at all stations where marine sediments are collected, including
anthracene, retene and napthalene. The total PAHs measured at WWTP B in 2009
range from 180-500 ng/g while at WWTP A in 2009, total PAHs range from 250-2600
ng/g. At WWTP B, there were 5 individual PAHs that were found to be above Canadian
Council of Ministers of the Environment (CCME) sediment quality guidelines (SQGs) at
one or more stations, while at WWTP A, all 17 PAHs for which CCME SQGs were
available, were above the guideline at one or more stations. (McPherson et al. 2010 a,b)
Even though we are unable to identify any PAHs using GC-MSD analysis, the fact that
the range of NAPEQs we estimated from the AhR assay are comparable to the total
PAHs in historical data at the same site suggests the total PAH concentrations in the
sediments at both sites have remained relatively unchanged. In other words, the
NAPEQs estimates in the present study indicate they may pose health risks to the
aquatic organisms living in the WWTP B and WWTP A sampling area.
Although no specific PAHs have been detected in the present study, one
chemical that has been identified in the marine sediments at both WWTP A and WWTP
B is dehydroabietic acid (DHAA) (Appendix H), a resin acid that is naturally found in
many coniferous trees (Martin et al. 1999). DHAA is commonly found in pulp and paper
mill effluents and is readily reduced by microorganisms under anaerobic conditions into
retene, a PAH (Ramanen et al. 2010, Leppanen and Oikari, 2001 and Martin et al.
1999). The presence of DHAA in the sediment suggests that the AhR activity seen in the
66
yeast AhR bioassay is due in part to the formation of retene which had also been
identified in a previous study conducted by Metro Vancouver. In 2012, retene
concentrations reported in marine sediment samples from WWTP A ranged from 17.9 to
105 ng/g, whereas concentrations at WWTP B ranged from 23.2 to 65.8 ng/g (Golder,
2013). The absence of DHAA from WWTP effluents indicates that sources other than
WWTPs are contributing to the AhR activity found in the marine sediments. This may
include pulp and paper mills, ship activity and other upstream industrial activities.
The endocrine disrupting properties of DHAA have been studied in organisms
such as the Rainbow trout (Oncorhynchus mykiss). Exposure of rainbow trout to DHAA
resulted in a reduction in vitellogenin levels indicating a potential anti-estrogenic effect of
DHAA (Orrego et al. 2010). A yeast two-hybrid assay testing resin acids including DHAA
confirms the anti-estrogenic potential of these chemicals. Although it was reported that
the mechanism of anti-estrogenicity of DHAA is not receptor-mediated as DHAA does
not show any affinity to the estrogen receptor, the YES bioassay may still be inhibited
(Terasaki et al. 2009). It is a possibility that the presence of DHAA in the marine
sediment had an effect on the EEQs estimated in the yeast estrogenic bioassay, leading
to an underestimation of the total estrogenic activity.
The identification of DHAA in marine sediments suggests that pulp and paper mill
effluents likely contributed to the load of EDCs measured through the yeast bioassay.
This may explain some of the estrogenic activity seen in the results as natural
phytoestrogens such as genistein have been detected in wood pulp at concentrations in
the µg/kg range and both treated and untreated mill effluents in the µg/L range
(Kiparissis et al. 2001). The presence of phytoestrogens in pulp mill effluents has been
thought to be a contributing factor in the reduction of reproductive capacity in fish and
other aquatic organisms. It has been shown that Japanese medaka exposed to genistein
show increased instances of gonadal intersex as well as alterations to secondary
characteristics (Kiparassis et al. 2003). In addition, genistein has also been reported to
induce apoptosis in zebrafish embryos through an ER independent pathway, but can
also activate 3 different zebrafish ERs leading to changes in the expression of
aromatase, an enzyme important in estrogen biosynthesis (Sassi-Messai et al. 2009). It
is therefore important to not only monitor concentrations of synthetic estrogens, but also
67
phytoestrogens as they are also capable of inducing adverse effects in aquatic
organisms.
4.8. Application of the Yeast Bioassay
The results of this study show that the yeast bioassay can be successfully
applied to different environmental samples for EDC detection. In addition, the assay is
suitable to screen for a large number of samples due to its relatively short run time of 6
hours. Other yeast or mammalian cell based assays used in the detection of EDCs have
run times generally ranging from 2-4 days (Bistan et al. 2011, Dagnino et al. 2010,
Sonneveld et al. 2005). The high throughput of samples allow for quick identification of
potentially contaminated sites where samples can be collected for further chemical
analysis.
Although the yeast bioassay is applicable in the detection of EDCs as well as
providing an estimation of potency, it should not be used as a standalone tool for
assessing EDC concentrations in environmental samples. Due to the variability of the
yeast assay, the estimated EDC concentrations should not be taken at face value even if
sufficient replication reduces the variation. The estimations are meant to identify sites
with the detectable concentrations of EDCs for further studies through other techniques
such as chemical analysis. Another issue encountered in this study is the presence of
compounds toxic to the yeast cells. Even though there are cleanup procedures such as
the sulphur removal procedure applied to the biosolids in this study, it is difficult to know
which cleanup procedure should be used when the structure of the toxic compounds in
the sample are not known. A second complication with the use of cleanup procedures is
the potential to remove target compounds from the sample extract. As no extraction
process is 100% efficient, any additional procedures applied to the sample extract may
cause loss of the target compounds, leading to an underestimation of the concentration
in the sample. Nonetheless, the yeast bioassay remains effective as a screening tool for
EDCs in both WWTP and environmental samples, though less effective when sample
activities are generally low.
68
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Appendix A. E2 and AhR Assay Results for Wastewater
2012 E2 Assay Results
WWTP EEQ (ng/L) Influent
Standard Deviation
EEQ (ng/L) Effluent
Standard Deviation
WWTP C 1.99 1.95 < MLOD -
6.46 < MLOD
6.21 4.41
5.72 < MLOD
3.49 < MLOD
WWTP D < MLOD - 0.32 0.57
< MLOD 1.32
< MLOD 1.32
WWTP A T - < MLOD -
T < MLOD
T < MLOD
T < MLOD
T < MLOD
WWTP B < MLOD - < MLOD -
< MLOD < MLOD
< MLOD < MLOD
WWTP E T T
T - T -
T T
T T
81
2013 E2 Assay Results
WWTP EEQ (ng/L) Influent
Standard Deviation
EEQ (ng/L) Effluent
Standard Deviation
WWTP C 9.37 7.42 1.08 0.30
2.28 0.69
19.96 1.17
< MLOD 1.36
7.48 1.50
WWTP D < MLOD - 1.52 0.62
< MLOD < MLOD
< MLOD < MLOD
< MLOD 2.44
WWTP A T 1.28 < MLOD -
T < MLOD
T < MLOD
2.51 < MLOD
4.16 < MLOD
WWTP B < MLOD - < MLOD -
< MLOD < MLOD
5.79 < MLOD
< MLOD < MLOD
WWTP E T - 1.30 0.52
T 2.40
T 1.77
T 1.69
T 1.07
82
2012 AhR Assay Results
WWTP NAPEQ (ng/L) Influent
Standard Deviation
NAPEQ (ng/L)
Effluent
Standard Deviation
WWTP C 97.84 68.47 45.58 44.02
232.43 < MLOD
170.35 131.16
58.51 < MLOD
172.82 70.46
WWTP D 237.61 12.78 < MLOD -
244.83 < MLOD
219.97 < MLOD
WWTP A < MLOD 105.75 138.51 91.15
< MLOD 151.63
266.27 302.55
79.80 < MLOD
85.58 < MLOD
WWTP B < MLOD - < MLOD -
< MLOD < MLOD
< MLOD < MLOD
WWTP E T T
T - T -
T T
T T
83
2013 AhR Assay Results
WWTP NAPEQ (ng/L) Influent
Standard Deviation
NAPEQ (ng/L)
Effluent
Standard Deviation
WWTP C 65.30 434.13 < MLOD 12.78
971.48 < MLOD
96.81 < MLOD
< MLOD < MLOD
598.01 76.98
WWTP D 139.54 72.94 92.20 6.83
274.09 82.37
105.01 82.54
171.10 95.83
WWTP A T - < MLOD -
T < MLOD
T < MLOD
T < MLOD
T < MLOD
WWTP B < MLOD 33.24 < MLOD 38.17
< MLOD < MLOD
132.29 121.13
29.43 < MLOD
WWTP E T - < MLOD -
T < MLOD
T < MLOD
T < MLOD
84
Appendix B. E2 and AhR Assay Results for Biosolids
E2 Assay Results
WWTP EEQ (ng/g) 2012 Standard Deviation
EEQ (ng/g) 2013
Standard Deviation
WWTP C 25.15 4.19 20.62 9.89
< MLOD 22.24
< MLOD 42.36
19.78 27.62
WWTP D 26.65 12.72 62.83 17.23
54.55 55.47
50.40 51.81
50.45 23.48
WWTP A 123.78 - T -
T T
T T
T T
85
AhR Assay Results
WWTP NAPEQ (ng/g) 2012
Standard Deviation
NAPEQ (ng/g) 2013
Standard Deviation
WWTP C 7274.07 2685.74 4590.16 1457.21
1900.26 4031.13
2968.91 2141.26
1350.84 1562.13
WWTP D 1043.41 284.89 784.82 542.37
418.25 1503.06
746.12 1405.77
483.14 2109.76
WWTP A 6716.91 646.92 9174.84 -
8009.75 T
7318.85 T
T T
86
Appendix C. E2 and AhR Assay Results for IDZ
WWTP C IDZ E2 and AhR Assay Results
Station EEQ (ng/L) Standard Deviation
NAPEQ (ng/L)
Standard Deviation
R1 < MLOD - < MLOD -
R2 < MLOD - < MLOD -
1 < MLOD - < MLOD -
2 3.38 2.23 < MLOD -
3 < MLOD - < MLOD -
4 < MLOD - < MLOD -
5A 1.67 0.73 < MLOD -
5B 2.09 0.82 < MLOD -
Effluent 1.66 1.11 138.38 98.32
87
WWTP A IDZ E2 and AhR Assay Results
Station EEQ (ng/L) Standard Deviation
NAPEQ (ng/L)
Standard Deviation
R1 < MLOD - < MLOD -
R2 < MLOD - < MLOD -
1 < MLOD - < MLOD -
2 < MLOD - < MLOD -
3 < MLOD - < MLOD -
4 < MLOD - < MLOD -
5A < MLOD - < MLOD -
5B < MLOD - < MLOD -
Effluent < MLOD - < MLOD -
88
Appendix D. E2 Assay Results for WWTP B Marine Sediments
Station EEQ (ng/g) 2012 Standard Deviation
EEQ (ng/g) 2013
Standard Deviation
1 < MLOD - 7.2 3.78
2 9.55 1.23 12.45 12.43
3 5.46 5.70 < MLOD -
4 < MLOD - < MLOD -
5 < MLOD - < MLOD -
6 < MLOD - < MLOD -
7 < MLOD - <MLOD -
<MLOD -
8 < MLOD - < MLOD -
<MLOD -
9 16.46 15.64 11.07 9.49
10 9.21 4.45 10.26 10.28
11 4.03 1.67 < MLOD -
12 < MLOD - 9.56 11.50
13 3.83 2.15 < MLOD -
14 11.16 0.96 < MLOD -
15 9.33 0.85 9.27 10.57
13.09 4.67
16 < MLOD - 9.99 10.99
10.99 2.50
89
Appendix E. E2 Assay Results for WWTP A Marine Sediments
Station EEQ (ng/g) 2012 Standard Deviation
EEQ (ng/g) 2013
Standard Deviation
4 < MLOD
< MLOD
- < MLOD -
5 51.94 30.56 24.02 8.75
30.94 12.54
3 25.94 18.99 49.42 41.19
16 < MLOD - < MLOD -
18 < MLOD - 30.63 28.077
11 < MLOD - 12.055 4.82
10 < MLOD - < MLOD -
46 < MLOD - < MLOD -
13 < MLOD - < MLOD -
12 < MLOD - < MLOD -
1 19.58 1.38 13.19 3.68
<MLOD - 13.20 2.911
2 32.94 12.01 < MLOD -
47 < MLOD - < MLOD -
45 36.31 26.63 39.24 33.71
<MLOD -
49 1.63 0.62 < MLOD -
6 < MLOD - < MLOD -
90
Appendix F. AhR Assay Results for WWTP B Marine Sediments
Station NAPEQ (ng/g) 2012
Standard Deviation
NAPEQ (ng/g) 2013
Standard Deviation
1 < MLOD - < MLOD -
2 < MLOD - 104.68 49.31
3 394.00 85.00 < LOD -
4 < MLOD - 255.75 57.66
5 < MLOD - 519.40 143.26
6 < MLOD - 505.83 119.89
7 < MLOD - < MLOD -
< MLOD -
8 < MLOD - 466.74 103.08
< MLOD -
9 < MLOD - < MLOD -
10 < MLOD - < MLOD -
11 < MLOD - < MLOD -
12 < MLOD - < MLOD -
13 < MLOD - < MLOD -
14 < MLOD - < MLOD -
15 < MLOD - 423.05 76.55
< MLOD -
16 533.00 32.00 483.13 126.33
360.82 82.56
91
Appendix G. AhR Assay Results for WWTP A Marine Sediments
Station NAPEQ (ng/g) 2012
Standard Deviation
NAPEQ (ng/g) 2013
Standard Deviation
4 < LOD - 551.15 11.14
5 < MLOD - < MLOD -
< MLOD -
3 453.00 155.00 < MLOD -
16 < MLOD - 871.35 601.13
18 1575.00 398.00 360.76 53.43
11 < MLOD - 361.13 123.52
10 517.00 121.00 518.05 131.50
46 < MLOD - < MLOD -
13 264.00 238.00 467.97 143.26
12 565.00 142.00 288.07 132.62
1 689.00 174.01 723.23 159.57
398.00 88.32 909.88 565.08
2 591.00 233.00 447.13 111.26
47 455.00 72.00 741.88 396.64
45 496.00 55.00 342.32 23.67
564.36 256.03
49 1219.00 144.00 1396.43 1132.59
6 297.00 159.00 < MLOD -
92
Appendix H. GC-MS Library Searches for BPA and DHAA
Bisphenol A
93
Dehydroabietic acid
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